From 333c2889bd3e5a6c94543a5af05fc6c27fc81fa3 Mon Sep 17 00:00:00 2001 From: Olivier CARON <78161167+oliviercaron@users.noreply.github.com> Date: Fri, 20 Oct 2023 17:15:24 +0200 Subject: [PATCH] up edge clickable --- .ipynb_checkpoints/Untitled-checkpoint.ipynb | 6 - .../sigmagrid_test-checkpoint.ipynb | 484 + list_ref_test_to_delete.csv | 27711 ++++++++++++ networks.qmd | 34 +- networks/authors/2013-2017_sigma.html | 226 +- networks/authors/2018-2021_sigma.html | 212 +- networks/authors/2022-2023_sigma.html | 36937 +++++++++++++++- networks/authors/before-2013_sigma.html | 234 +- .../network_2022_2023_louvain_pyvis.html | 2 +- networks/authors/network_2022_2023_pyvis.html | 2 +- networks/references/2022_2023_sigma.html | 33533 +------------- sigmagrid_test.ipynb | 484 + 12 files changed, 67375 insertions(+), 32490 deletions(-) delete mode 100644 .ipynb_checkpoints/Untitled-checkpoint.ipynb create mode 100644 .ipynb_checkpoints/sigmagrid_test-checkpoint.ipynb create mode 100644 list_ref_test_to_delete.csv create mode 100644 sigmagrid_test.ipynb diff --git a/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/.ipynb_checkpoints/Untitled-checkpoint.ipynb deleted file mode 100644 index 363fcab..0000000 --- a/.ipynb_checkpoints/Untitled-checkpoint.ipynb +++ /dev/null @@ -1,6 +0,0 @@ -{ - "cells": [], - "metadata": {}, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/.ipynb_checkpoints/sigmagrid_test-checkpoint.ipynb b/.ipynb_checkpoints/sigmagrid_test-checkpoint.ipynb new file mode 100644 index 0000000..dec772f --- /dev/null +++ b/.ipynb_checkpoints/sigmagrid_test-checkpoint.ipynb @@ -0,0 +1,484 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 81, + "id": "56f012f3", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import networkx as nx\n", + "import matplotlib.pyplot as plt\n", + "import plotly.express as px\n", + "from datetime import datetime\n", + "import re\n", + "from ipysigma import Sigma, SigmaGrid" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "35fab3df", + "metadata": {}, + "outputs": [], + "source": [ + "list_references = pd.read_csv(\"list_ref_test_to_delete.csv\", sep=';', decimal=',')\n", + "data = pd.read_csv(\"data_final.csv\")\n", + "data.rename(columns={'citedby-count': 'citedby_count'}, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "id": "2b51f9d3", + "metadata": {}, + "outputs": [], + "source": [ + "def sort_dict(dict):\n", + " sorted_dict = {k: v for k, v in sorted(dict.items(), key=lambda item: item[0])}\n", + " return sorted_dict" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "id": "ed6136db", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "def get_citations_df(df, start_year=None, end_year=None):\n", + " \"\"\"\n", + " Filter and extract necessary columns for citation network from a DataFrame based on a range of years.\n", + " \n", + " Parameters:\n", + " - df: DataFrame containing the data\n", + " - start_year: Optional, the starting year for filtering\n", + " - end_year: Optional, the ending year for filtering\n", + " \n", + " Returns:\n", + " - DataFrame with filtered data\n", + " \"\"\"\n", + " \n", + " # Replace 'NA' with numpy.nan and reassign the DataFrame\n", + " df = df.replace({'year': 'NA'}, np.nan)\n", + " \n", + " # Drop rows where 'year' is NaN\n", + " df = df.dropna(subset=['year'])\n", + " \n", + " # Convert the 'year' column to integer using .astype\n", + " df['year'] = df['year'].astype(int)\n", + " \n", + " # Filter the data based on the 'year' column only if start_year and end_year are provided\n", + " if start_year is not None and end_year is not None:\n", + " df = df[df['year'].between(start_year, end_year)]\n", + " \n", + " # Extract necessary columns for the citation network\n", + " citations_df = df[['citing_art', 'scopus_id', 'sourcetitle', 'title', 'citedby_count', 'citations_per_year' , 'author', 'year']]\n", + " \n", + " return citations_df\n", + "\n", + "# Using the function to get a->b standardized data for the citations networks below\n", + "citations_df_2022_2023 = get_citations_df(list_references_standardized, 2022, 2023)\n", + "citations_df_2018_2021 = get_citations_df(list_references_standardized, 2018, 2021)\n", + "citations_df_2013_2017 = get_citations_df(list_references_standardized, 2013, 2017)\n", + "citations_df_before_2013 = get_citations_df(list_references_standardized, 0, 2012)\n", + "citations_df_overall = get_citations_df(list_references_standardized) #No filter on years: " + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "id": "7528e411", + "metadata": {}, + "outputs": [], + "source": [ + "def standardize_values(df, groupby_column, value_column):\n", + " \"\"\"\n", + " Standardize the values of the specified column based on the most frequent non-empty value and fewest characters \n", + " within each group.\n", + "\n", + " Parameters:\n", + " - df: DataFrame\n", + " - groupby_column: The column by which we group data.\n", + " - value_column: The column whose values we want to standardize based on the rules.\n", + "\n", + " Returns:\n", + " - DataFrame with standardized values.\n", + " \"\"\"\n", + " \n", + " def custom_mode(series):\n", + " # Remove NA values and other representations of NA\n", + " series = series.dropna()\n", + " series = series[~series.isin(['', 'NA'])]\n", + " \n", + " # If all values were NA or empty\n", + " if series.empty:\n", + " return np.nan # Using numpy's nan for consistency\n", + "\n", + " # Get value counts\n", + " counts = series.value_counts()\n", + "\n", + " # If there's a single most common value, return it\n", + " if len(counts) == 1 or counts.iloc[0] != counts.iloc[1]:\n", + " return counts.idxmax()\n", + "\n", + " # If multiple values have the same max count, apply further rules\n", + " top_values = counts[counts == counts.iloc[0]].index.tolist()\n", + "\n", + " # Sort by fewest characters\n", + " sorted_by_chars = sorted(top_values, key=lambda x: len(x))\n", + "\n", + " # If there's a single value with the fewest characters, return it\n", + " if len(sorted_by_chars) == 1 or len(sorted_by_chars[0]) != len(sorted_by_chars[1]):\n", + " return sorted_by_chars[0]\n", + "\n", + " # If the column is not the author's name, apply the uppercase letter rule.\n", + " if value_column != \"author_name\": # adjust \"author_name\" to the correct column name if necessary\n", + " return sorted(sorted_by_chars, key=lambda x: sum(1 for c in x if c.isupper()), reverse=True)[0]\n", + " else:\n", + " return sorted_by_chars[0]\n", + "\n", + " # Find the most common value for each group based on the custom mode\n", + " most_common_value = df.groupby(groupby_column)[value_column].apply(custom_mode).to_dict()\n", + "\n", + " # Map the most common values to the dataframe based on the group\n", + " df[value_column] = df[groupby_column].map(most_common_value)\n", + "\n", + " return df\n", + "\n", + "\n", + "# Usage example:\n", + "list_references_standardized = standardize_values(list_references, 'scopus_id', 'title')\n", + "list_references_standardized = standardize_values(list_references_standardized, 'scopus_id', 'sourcetitle')\n", + "list_references_standardized = standardize_values(list_references_standardized, 'scopus_id', 'author')" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "id": "b4bce5b8", + "metadata": {}, + "outputs": [], + "source": [ + "def get_citations_df(df, start_year=None, end_year=None):\n", + " \"\"\"\n", + " Filter and extract necessary columns for citation network from a DataFrame based on a range of years.\n", + " \n", + " Parameters:\n", + " - df: DataFrame containing the data\n", + " - start_year: Optional, the starting year for filtering\n", + " - end_year: Optional, the ending year for filtering\n", + " \n", + " Returns:\n", + " - DataFrame with filtered data\n", + " \"\"\"\n", + " \n", + " # Replace 'NA' with numpy.nan and reassign the DataFrame\n", + " df = df.replace({'year': 'NA'}, np.nan)\n", + " \n", + " # Drop rows where 'year' is NaN\n", + " df = df.dropna(subset=['year'])\n", + " \n", + " # Convert the 'year' column to integer using .astype\n", + " df['year'] = df['year'].astype(int)\n", + " \n", + " # Filter the data based on the 'year' column only if start_year and end_year are provided\n", + " if start_year is not None and end_year is not None:\n", + " df = df[df['year'].between(start_year, end_year)]\n", + " \n", + " # Extract necessary columns for the citation network\n", + " citations_df = df[['citing_art', 'scopus_id', 'sourcetitle', 'title', 'citedby_count', 'citations_per_year' , 'author', 'year']]\n", + " \n", + " return citations_df\n", + "\n", + "# Using the function to get a->b standardized data for the citations networks below\n", + "citations_df_2022_2023 = get_citations_df(list_references_standardized, 2022, 2023)\n", + "citations_df_2018_2021 = get_citations_df(list_references_standardized, 2018, 2021)\n", + "citations_df_2013_2017 = get_citations_df(list_references_standardized, 2013, 2017)\n", + "citations_df_before_2013 = get_citations_df(list_references_standardized, 0, 2012)\n", + "citations_df_overall = get_citations_df(list_references_standardized) #No filter on years: " + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "id": "71ba97a2", + "metadata": {}, + "outputs": [], + "source": [ + "def get_info_references_dict(df, key, column):\n", + " \"\"\"\n", + " Create a dictionary with keys from the specified key_column and values from the specified value_column.\n", + "\n", + " :param df: Input DataFrame.\n", + " :param key_column: Column name to be used as keys in the resulting dictionary.\n", + " :param value_column: Column name to be used as values in the resulting dictionary.\n", + " :return: Dictionary with keys from key_column and values from value_column.\n", + " \"\"\"\n", + " if key not in df.columns or column not in df.columns:\n", + " raise ValueError(\"The required columns are not present in the DataFrame.\")\n", + " return sort_dict(df.set_index(key)[column].to_dict())\n", + " \n", + "\n", + "# We also need to get the info of the citing articles, otherwise we won't get any info when we click \n", + "# on the nodes and we will have the number of the node as node label instead of the author name\n", + "# Create the 'citing_art' column by stripping the first 10 characters from 'dc_identifier'\n", + "data['citing_art'] = data['dc_identifier'].str[10:]\n", + "\n", + "# Getting the current year\n", + "current_year = datetime.now().year\n", + "\n", + "# English Comment: Function to calculate citations per year, handles NaN values, division by zero, and the current year.\n", + "def calculate_citations_per_year(row):\n", + " if pd.isna(row['year']):\n", + " return np.nan\n", + " elif (current_year - row['year']) == 0:\n", + " return 0 # Handle division by zero by returning 0\n", + " else:\n", + " return round(row['citedby_count'] / (current_year - row['year']), 2)\n", + "\n", + "# Creating the new column 'citations_per_year'\n", + "data['citations_per_year'] = data.apply(calculate_citations_per_year, axis=1)\n", + "\n", + "# List of columns to use in the networks later as attributes. We can add more columns if we want to.\n", + "columns_to_extract = ['title', 'sourcetitle', 'citedby_count', 'author', 'year', 'citations_per_year']\n", + "\n", + "# Dictionary of dataframes with their respective names\n", + "dfs = {\n", + " \"2022_2023\": citations_df_2022_2023,\n", + " \"2018_2021\": citations_df_2018_2021,\n", + " \"2013_2017\": citations_df_2013_2017,\n", + " \"before_2013\": citations_df_before_2013,\n", + " \"overall\": citations_df_overall\n", + "}\n", + "\n", + "\n", + "# Map old column names to new column names\n", + "column_mapping = {\n", + " 'title': 'dc_title',\n", + " 'sourcetitle': 'prism_publicationName',\n", + " 'author': 'dc_creator',\n", + " 'year': 'year',\n", + " 'citations': 'citedby_count',\n", + " 'citations_per_year': 'citations_per_year'\n", + "}\n", + "\n", + "# Reverse mapping for merging\n", + "reverse_column_mapping = {v: k for k, v in column_mapping.items()}\n", + "\n", + "# Rename columns in data DataFrame for merging\n", + "data.rename(columns=reverse_column_mapping, inplace=True)\n", + "\n", + "\n", + "# Initialize the output dictionary\n", + "dict_references = {}\n", + "\n", + "# Retrieve the information for each period and each column\n", + "for period, df in dfs.items():\n", + " dict_references[period] = {}\n", + " for column in columns_to_extract:\n", + " # This check is important in case all columns are not present across all dataframes\n", + " if column in df.columns:\n", + " dict_references[period][column] = get_info_references_dict(df, 'scopus_id', column)\n", + "\n", + " # Get the citing_art dictionary from 'data' DataFrame\n", + " for column in columns_to_extract:\n", + " if column in data.columns:\n", + " citing_art_dict = get_info_references_dict(data, 'citing_art', column)\n", + " \n", + " # Add to dict_references only if key is not already present \n", + " # It means that the article in our data has been cited by others and is then already present in the references dataframe\n", + " for key, value in citing_art_dict.items():\n", + " if key not in dict_references[period].get(column, {}):\n", + " dict_references[period].setdefault(column, {})[key] = value\n" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "id": "fb80c28a", + "metadata": {}, + "outputs": [], + "source": [ + "def sigma_graph_references(dataframe, period_label):\n", + " \n", + " # Create a graph from the given dataframe\n", + " G = nx.from_pandas_edgelist(dataframe, 'citing_art', 'scopus_id', create_using=nx.DiGraph())\n", + " \n", + " # Fetch attributes for the given period from the global dict_references\n", + " attributes_dict = dict_references.get(period_label, {})\n", + "\n", + " # Set the attributes from dict_references to the nodes of the graph\n", + " for attribute, attribute_dict in attributes_dict.items():\n", + " nx.set_node_attributes(G, attribute_dict, name=attribute)\n", + "\n", + " # Set edge colors for visualization\n", + " for u, v in G.edges:\n", + " G[u][v][\"color\"] = \"#7D7C7C\"\n", + "\n", + " # Calculate the degree of each node\n", + " node_degree = dict(G.degree)\n", + "\n", + " # Compute multiple centrality metrics for nodes\n", + " node_degree_centrality = nx.degree_centrality(G)\n", + " node_degree_betweenness = nx.betweenness_centrality(G)\n", + " node_degree_closeness = nx.closeness_centrality(G)\n", + " node_degree_eigenvector = nx.closeness_centrality(G)\n", + " #node_degree_constraint_weighted = nx.constraint(G, weight=\"value\")\n", + " node_degree_constraint_unweighted = nx.constraint(G)\n", + " \n", + " # Set node attributes for various metrics\n", + " nx.set_node_attributes(G, node_degree_centrality, 'centrality')\n", + " nx.set_node_attributes(G, node_degree_betweenness, 'betweenness')\n", + " nx.set_node_attributes(G, node_degree_closeness, 'closeness')\n", + " nx.set_node_attributes(G, node_degree_eigenvector, 'eigenvector centrality')\n", + " #nx.set_node_attributes(G, node_degree_constraint_weighted, 'burt\\'s constraint weighted')\n", + " nx.set_node_attributes(G, node_degree_constraint_unweighted, 'burt constraint unweighted')\n", + " \n", + " # Set node attributes based on the selected 'year_period'\n", + " \n", + "\n", + " # Construct the sigma graph and customize visualization\n", + " Sigma.write_html(G,\n", + " default_edge_type = \"arrow\", # Set default edge type\n", + " fullscreen = True, # Display in fullscreen mode\n", + " label_density = 2, # Increase this to have more labels appear\n", + " label_font = \"Helvetica Neue\", # Set label font\n", + " max_categorical_colors = 30, # Max categorical colors for communities\n", + " node_border_color_from = 'node', # Set node border color from 'node' attribute\n", + " node_color = \"community\", # Set node colors\n", + " node_label = \"author\", # Set node label from 'author' attribute\n", + " node_label_size = G.in_degree, # Set node label size\n", + " node_label_size_range = (12, 36), # Set node label size range\n", + " node_metrics = {\"community\": {\"name\": \"louvain\", \"resolution\": 1}}, # Specify node metrics\n", + " node_size = G.in_degree, # Set node size based on the in_degree attribute\n", + " node_size_range = (3, 30), # Set node size range\n", + " path = f\"networks/references/{period_label}_sigma.html\", # Specify the output file path\n", + " start_layout = 10 # Start the layout algorithm automatically and lasts 5 seconds\n", + " #node_border_color = \"black\", # Set node border color\n", + " #edge_color = \"source\", # Set edge color from 'source' attribute\n", + " )\n", + "\n", + " return G" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "id": "3aa4f1dc", + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "Object of type builtin_function_or_method is not JSON serializable", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[93], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m G_2022_2023_references \u001b[38;5;241m=\u001b[39m sigma_graph_references(citations_df_2022_2023, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m2022_2023\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "Cell \u001b[1;32mIn[92], line 40\u001b[0m, in \u001b[0;36msigma_graph_references\u001b[1;34m(dataframe, period_label)\u001b[0m\n\u001b[0;32m 34\u001b[0m nx\u001b[38;5;241m.\u001b[39mset_node_attributes(G, node_degree_constraint_unweighted, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mburt constraint unweighted\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 36\u001b[0m \u001b[38;5;66;03m# Set node attributes based on the selected 'year_period'\u001b[39;00m\n\u001b[0;32m 37\u001b[0m \n\u001b[0;32m 38\u001b[0m \n\u001b[0;32m 39\u001b[0m \u001b[38;5;66;03m# Construct the sigma graph and customize visualization\u001b[39;00m\n\u001b[1;32m---> 40\u001b[0m Sigma\u001b[38;5;241m.\u001b[39mwrite_html(G,\n\u001b[0;32m 41\u001b[0m default_edge_type \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124marrow\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Set default edge type\u001b[39;00m\n\u001b[0;32m 42\u001b[0m fullscreen \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m, \u001b[38;5;66;03m# Display in fullscreen mode\u001b[39;00m\n\u001b[0;32m 43\u001b[0m label_density \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;66;03m# Increase this to have more labels appear\u001b[39;00m\n\u001b[0;32m 44\u001b[0m label_font \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mHelvetica Neue\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Set label font\u001b[39;00m\n\u001b[0;32m 45\u001b[0m max_categorical_colors \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m30\u001b[39m, \u001b[38;5;66;03m# Max categorical colors for communities\u001b[39;00m\n\u001b[0;32m 46\u001b[0m node_border_color_from \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnode\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;66;03m# Set node border color from 'node' attribute\u001b[39;00m\n\u001b[0;32m 47\u001b[0m node_color \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcommunity\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Set node colors\u001b[39;00m\n\u001b[0;32m 48\u001b[0m node_label \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mauthor\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Set node label from 'author' attribute\u001b[39;00m\n\u001b[0;32m 49\u001b[0m node_label_size \u001b[38;5;241m=\u001b[39m G\u001b[38;5;241m.\u001b[39min_degree, \u001b[38;5;66;03m# Set node label size\u001b[39;00m\n\u001b[0;32m 50\u001b[0m node_label_size_range \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m12\u001b[39m, \u001b[38;5;241m36\u001b[39m), \u001b[38;5;66;03m# Set node label size range\u001b[39;00m\n\u001b[0;32m 51\u001b[0m node_metrics \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcommunity\u001b[39m\u001b[38;5;124m\"\u001b[39m: {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlouvain\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresolution\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;241m1\u001b[39m}}, \u001b[38;5;66;03m# Specify node metrics\u001b[39;00m\n\u001b[0;32m 52\u001b[0m node_size \u001b[38;5;241m=\u001b[39m G\u001b[38;5;241m.\u001b[39min_degree, \u001b[38;5;66;03m# Set node size based on the in_degree attribute\u001b[39;00m\n\u001b[0;32m 53\u001b[0m node_size_range \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m3\u001b[39m, \u001b[38;5;241m30\u001b[39m), \u001b[38;5;66;03m# Set node size range\u001b[39;00m\n\u001b[0;32m 54\u001b[0m path \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnetworks/references/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mperiod_label\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_sigma.html\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Specify the output file path\u001b[39;00m\n\u001b[0;32m 55\u001b[0m start_layout \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m10\u001b[39m \u001b[38;5;66;03m# Start the layout algorithm automatically and lasts 5 seconds\u001b[39;00m\n\u001b[0;32m 56\u001b[0m \u001b[38;5;66;03m#node_border_color = \"black\", # Set node border color\u001b[39;00m\n\u001b[0;32m 57\u001b[0m \u001b[38;5;66;03m#edge_color = \"source\", # Set edge color from 'source' attribute\u001b[39;00m\n\u001b[0;32m 58\u001b[0m )\n\u001b[0;32m 60\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m G\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\ipysigma\\sigma.py:1143\u001b[0m, in \u001b[0;36mSigma.write_html\u001b[1;34m(cls, graph, path, fullscreen, **kwargs)\u001b[0m\n\u001b[0;32m 1140\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mheight\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 1141\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mraw_height\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcalc(100vh - 16px)\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m-> 1143\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(graph, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\u001b[38;5;241m.\u001b[39mto_html(path)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\ipysigma\\sigma.py:1133\u001b[0m, in \u001b[0;36mSigma.to_html\u001b[1;34m(self, path)\u001b[0m\n\u001b[0;32m 1130\u001b[0m current_snapshot \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msnapshot\n\u001b[0;32m 1131\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msnapshot \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m-> 1133\u001b[0m embed_minimal_html(path, views\u001b[38;5;241m=\u001b[39m[\u001b[38;5;28mself\u001b[39m])\n\u001b[0;32m 1135\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msnapshot \u001b[38;5;241m=\u001b[39m current_snapshot\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\ipywidgets\\embed.py:302\u001b[0m, in \u001b[0;36membed_minimal_html\u001b[1;34m(fp, views, title, template, **kwargs)\u001b[0m\n\u001b[0;32m 286\u001b[0m \u001b[38;5;129m@doc_subst\u001b[39m(_doc_snippets)\n\u001b[0;32m 287\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21membed_minimal_html\u001b[39m(fp, views, title\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mIPyWidget export\u001b[39m\u001b[38;5;124m'\u001b[39m, template\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 288\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Write a minimal HTML file with widget views embedded.\u001b[39;00m\n\u001b[0;32m 289\u001b[0m \n\u001b[0;32m 290\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 300\u001b[0m \u001b[38;5;124;03m {embed_kwargs}\u001b[39;00m\n\u001b[0;32m 301\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 302\u001b[0m snippet \u001b[38;5;241m=\u001b[39m embed_snippet(views, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m 304\u001b[0m values \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 305\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtitle\u001b[39m\u001b[38;5;124m'\u001b[39m: title,\n\u001b[0;32m 306\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msnippet\u001b[39m\u001b[38;5;124m'\u001b[39m: snippet,\n\u001b[0;32m 307\u001b[0m }\n\u001b[0;32m 308\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m template \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\ipywidgets\\embed.py:279\u001b[0m, in \u001b[0;36membed_snippet\u001b[1;34m(views, drop_defaults, state, indent, embed_url, requirejs, cors)\u001b[0m\n\u001b[0;32m 274\u001b[0m load \u001b[38;5;241m=\u001b[39m load_requirejs_template \u001b[38;5;28;01mif\u001b[39;00m requirejs \u001b[38;5;28;01melse\u001b[39;00m load_template\n\u001b[0;32m 276\u001b[0m use_cors \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m crossorigin=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124manonymous\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m cors \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m 277\u001b[0m values \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 278\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mload\u001b[39m\u001b[38;5;124m'\u001b[39m: load\u001b[38;5;241m.\u001b[39mformat(embed_url\u001b[38;5;241m=\u001b[39membed_url, use_cors\u001b[38;5;241m=\u001b[39muse_cors),\n\u001b[1;32m--> 279\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mjson_data\u001b[39m\u001b[38;5;124m'\u001b[39m: escape_script(json\u001b[38;5;241m.\u001b[39mdumps(data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmanager_state\u001b[39m\u001b[38;5;124m'\u001b[39m], indent\u001b[38;5;241m=\u001b[39mindent)),\n\u001b[0;32m 280\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mwidget_views\u001b[39m\u001b[38;5;124m'\u001b[39m: widget_views,\n\u001b[0;32m 281\u001b[0m }\n\u001b[0;32m 283\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m snippet_template\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mvalues)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\__init__.py:238\u001b[0m, in \u001b[0;36mdumps\u001b[1;34m(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)\u001b[0m\n\u001b[0;32m 232\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 233\u001b[0m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;241m=\u001b[39m JSONEncoder\n\u001b[0;32m 234\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(\n\u001b[0;32m 235\u001b[0m skipkeys\u001b[38;5;241m=\u001b[39mskipkeys, ensure_ascii\u001b[38;5;241m=\u001b[39mensure_ascii,\n\u001b[0;32m 236\u001b[0m check_circular\u001b[38;5;241m=\u001b[39mcheck_circular, allow_nan\u001b[38;5;241m=\u001b[39mallow_nan, indent\u001b[38;5;241m=\u001b[39mindent,\n\u001b[0;32m 237\u001b[0m separators\u001b[38;5;241m=\u001b[39mseparators, default\u001b[38;5;241m=\u001b[39mdefault, sort_keys\u001b[38;5;241m=\u001b[39msort_keys,\n\u001b[1;32m--> 238\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkw)\u001b[38;5;241m.\u001b[39mencode(obj)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:202\u001b[0m, in \u001b[0;36mJSONEncoder.encode\u001b[1;34m(self, o)\u001b[0m\n\u001b[0;32m 200\u001b[0m chunks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39miterencode(o, _one_shot\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m 201\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(chunks, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m)):\n\u001b[1;32m--> 202\u001b[0m chunks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(chunks)\n\u001b[0;32m 203\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(chunks)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:432\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode\u001b[1;34m(o, _current_indent_level)\u001b[0m\n\u001b[0;32m 430\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m _iterencode_list(o, _current_indent_level)\n\u001b[0;32m 431\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(o, \u001b[38;5;28mdict\u001b[39m):\n\u001b[1;32m--> 432\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m _iterencode_dict(o, _current_indent_level)\n\u001b[0;32m 433\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 434\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m markers \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:406\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode_dict\u001b[1;34m(dct, _current_indent_level)\u001b[0m\n\u001b[0;32m 404\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 405\u001b[0m chunks \u001b[38;5;241m=\u001b[39m _iterencode(value, _current_indent_level)\n\u001b[1;32m--> 406\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m chunks\n\u001b[0;32m 407\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m newline_indent \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 408\u001b[0m _current_indent_level \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:406\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode_dict\u001b[1;34m(dct, _current_indent_level)\u001b[0m\n\u001b[0;32m 404\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 405\u001b[0m chunks \u001b[38;5;241m=\u001b[39m _iterencode(value, _current_indent_level)\n\u001b[1;32m--> 406\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m chunks\n\u001b[0;32m 407\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m newline_indent \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 408\u001b[0m _current_indent_level \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n", + " \u001b[1;31m[... skipping similar frames: _make_iterencode.._iterencode_dict at line 406 (2 times)]\u001b[0m\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:406\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode_dict\u001b[1;34m(dct, _current_indent_level)\u001b[0m\n\u001b[0;32m 404\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 405\u001b[0m chunks \u001b[38;5;241m=\u001b[39m _iterencode(value, _current_indent_level)\n\u001b[1;32m--> 406\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m chunks\n\u001b[0;32m 407\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m newline_indent \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 408\u001b[0m _current_indent_level \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:439\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode\u001b[1;34m(o, _current_indent_level)\u001b[0m\n\u001b[0;32m 437\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCircular reference detected\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 438\u001b[0m markers[markerid] \u001b[38;5;241m=\u001b[39m o\n\u001b[1;32m--> 439\u001b[0m o \u001b[38;5;241m=\u001b[39m _default(o)\n\u001b[0;32m 440\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m _iterencode(o, _current_indent_level)\n\u001b[0;32m 441\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m markers \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:180\u001b[0m, in 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It could be helpful to retrieve these data so we can see them when we click on the nodes. ```{r} #| label: citations-get-missing-data-todo @@ -1271,7 +1274,6 @@ def sigma_graph_references(dataframe, period_label): return G - ``` ### Citations network for 2022-2023 ([click here for fullscreen](https://oliviercaron.github.io/systematic_lit_review/networks/references/2022_2023_sigma.html)) @@ -1286,6 +1288,20 @@ G_2022_2023_references = sigma_graph_references(citations_df_2022_2023, "2022_20 #df_sorted = df_burt_constraint.sort_values(by='Burt_Constraint_Unweighted') #print(df_sorted) +SigmaGrid.to_html( + G_2022_2023_references, + views=[{'node_size': G_2022_2023_references.in_degree}, {'node_size': 'citations_year'}], + node_size_range=(2, 10), + default_edge_type='curve', + path="networks/references/2022_2023_sigma_grid.html", +) + +SigmaGrid(G_2022_2023_references, + views=[{'node_size': G_2022_2023_references.in_degree}, {'node_size': 'citations_year'}], + node_size_range=(2, 10), + default_edge_type='curve', + #path="networks/references/2022_2023_sigma_grid.html" + ) ``` ```{=html} @@ -1347,6 +1363,7 @@ G_overall_references = sigma_graph_references(citations_df_overall, "overall") #| output: false + # Create a dataframe with the density of each graph density_df_references = pd.DataFrame({ 'period': ['before-2013', '2013-2017', '2018-2021', '2022-2023', 'overall'], @@ -1378,6 +1395,7 @@ density_df_references = pd.DataFrame({ ```{r} #| label: citations-graph-density-comparison #| fig.cap: Comparison of network densities and average degree of nodes over time +#| column: body-outset # Density plot density_plot <- ggplot() + @@ -1412,6 +1430,6 @@ avg_degree_plot <- ggplot() + # Combine density and average degree plots density_plot / linear_density_plot / avg_degree_plot -ggsave("images/citations-graph-density-comparison.png", width=27, height=18, units="cm", dpi=300) +ggsave("images/citations-graph-density-comparison.png", width=270, height=180, units="cm", dpi=300) ``` diff --git a/networks/authors/2013-2017_sigma.html b/networks/authors/2013-2017_sigma.html index be6e31b..22996f8 100644 --- a/networks/authors/2013-2017_sigma.html +++ b/networks/authors/2013-2017_sigma.html @@ -16,7 +16,7 @@ "version_major": 2, "version_minor": 0, "state": { - "b70656de701d4a6dbd06d730d5e500b5": { + "7356463a3e164d8290cefa6a8960790d": { "model_name": "SigmaModel", "model_module": "ipysigma", "model_module_version": "^0.24.2", @@ -463,8 +463,8 @@ "betweenness": 5.2630193942264676e-05, "closeness": 0.010460251046025104, "eigenvector centrality": 0.010460251046025104, - "burt's constraint weighted": 0.5133333333333334, - "burt's constraint unweighted": 0.5133333333333334, + "burt's constraint weighted": 0.5133333333333335, + "burt's constraint unweighted": 0.5133333333333335, "affiliation": "Villanova University | Villanova School of Business", "country": "United States", "articles": "It is not just a name: Effects of proper name for high-quality versus low-quality brands | Algorithms propagate gender bias in the marketplace\u2014with consumers\u2019 cooperation", @@ -512,7 +512,7 @@ "closeness": 0.014121338912133892, "eigenvector centrality": 0.014121338912133892, "burt's constraint weighted": 0.5076884631403582, - "burt's constraint unweighted": 0.4957098765432098, + "burt's constraint unweighted": 0.49570987654320975, "affiliation": "University of St. Gallen", "country": "Switzerland", "articles": "Voice bots on the frontline: Voice-based interfaces enhance flow-like consumer experiences & boost service outcomes | MindMiner: Uncovering linguistic markers of mind perception as a new lens to understand consumer\u2013smart object relationships", @@ -1177,7 +1177,7 @@ "betweenness": 0.00012280378586528425, "closeness": 0.021518230723251642, "eigenvector centrality": 0.021518230723251642, - "burt's constraint weighted": 0.3422454193829099, + "burt's constraint weighted": 0.34224541938291, "burt's constraint unweighted": 0.32514583333333336, "articles": "Complaint De-Escalation Strategies on Social Media | Communication in the Gig Economy: Buying and Selling in Online Freelance Marketplaces", "journals": "Journal of Marketing", @@ -1770,7 +1770,7 @@ "closeness": 0.009414225941422594, "eigenvector centrality": 0.009414225941422594, "burt's constraint weighted": 0.7152777777777777, - "burt's constraint unweighted": 0.7122395833333331, + "burt's constraint unweighted": 0.7122395833333333, "affiliation": "Iscte \u2013 Instituto Universit\u00e1rio de Lisboa", "country": "Portugal", "articles": "Discovering ethnic minority business research directions using text mining and topic modelling | Are social media and mobile applications threatening retail websites?", @@ -1786,7 +1786,7 @@ "closeness": 0.009414225941422594, "eigenvector centrality": 0.009414225941422594, "burt's constraint weighted": 0.7826605902777777, - "burt's constraint unweighted": 0.7122395833333331, + "burt's constraint unweighted": 0.7122395833333333, "affiliation": "Newcastle Business School", "country": "Australia", "articles": "Discovering ethnic minority business research directions using text mining and topic modelling", @@ -1818,7 +1818,7 @@ "closeness": 0.009414225941422594, "eigenvector centrality": 0.009414225941422594, "burt's constraint weighted": 0.7826605902777777, - "burt's constraint unweighted": 0.7122395833333331, + "burt's constraint unweighted": 0.7122395833333333, "affiliation": "Universidade do Minho", "country": "Portugal", "articles": "Discovering ethnic minority business research directions using text mining and topic modelling", @@ -1834,7 +1834,7 @@ "closeness": 0.009414225941422594, "eigenvector centrality": 0.009414225941422594, "burt's constraint weighted": 0.7152777777777777, - "burt's constraint unweighted": 0.7122395833333331, + "burt's constraint unweighted": 0.7122395833333333, "affiliation": "Instituto Politcnico de Coimbra", "country": "Portugal", "articles": "Discovering ethnic minority business research directions using text mining and topic modelling | Are social media and mobile applications threatening retail websites?", @@ -1896,7 +1896,7 @@ "closeness": 0.02109483960948396, "eigenvector centrality": 0.02109483960948396, "burt's constraint weighted": 0.3196763085399449, - "burt's constraint unweighted": 0.29859583333333334, + "burt's constraint unweighted": 0.2985958333333334, "affiliation": "King's College London", "country": "United Kingdom", "articles": "From Crisis to Advocacy: Tracing the Emergence and Evolution of the LGBTQIA+ Consumer Market | \u201cDoes It Go Without Saying?\u201d Implication of Electronic Word of Mouth in Luxury Branding: An Abstract | Studying the Effects of Sponsorship Disclosure and Message Complexity on Consumers\u2019 Response Via Text Analysis: An Abstract", @@ -2099,7 +2099,7 @@ "betweenness": 0.0, "closeness": 0.008368200836820083, "eigenvector centrality": 0.008368200836820083, - "burt's constraint weighted": 0.7751718034152435, + "burt's constraint weighted": 0.7751718034152437, "burt's constraint unweighted": 0.765625, "affiliation": "The University of Queensland Business School | Queensland University of Technology", "country": "Australia", @@ -2131,7 +2131,7 @@ "betweenness": 0.0, "closeness": 0.008368200836820083, "eigenvector centrality": 0.008368200836820083, - 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How expected and actual nutritional value affect the content and linguistic characteristics of online reviews for food products | Perception and gaze of diaspora: Analysis of affective, cognitive, & cultural factors in tourism", @@ -2211,8 +2211,8 @@ "betweenness": 0.0, "closeness": 0.010713832889565107, "eigenvector centrality": 0.010713832889565107, - "burt's constraint weighted": 0.7928949357520785, - "burt's constraint unweighted": 0.7928949357520785, + "burt's constraint weighted": 0.7928949357520786, + "burt's constraint unweighted": 0.7928949357520786, "affiliation": "Duquesne University", "country": "United States", "articles": "But it was supposed to be healthy! How expected and actual nutritional value affect the content and linguistic characteristics of online reviews for food products", @@ -2573,8 +2573,8 @@ "betweenness": 0.0, "closeness": 0.007471607890017932, "eigenvector centrality": 0.007471607890017932, - "burt's constraint weighted": 0.8311111111111109, - "burt's constraint unweighted": 0.8311111111111109, + "burt's constraint weighted": 0.831111111111111, + "burt's constraint unweighted": 0.831111111111111, "affiliation": "David Eccles School of Business", "country": "United States", "articles": "Algorithms propagate gender bias in the marketplace\u2014with consumers\u2019 cooperation", @@ -2765,8 +2765,8 @@ "betweenness": 0.00019297737778830383, "closeness": 0.023570432357043238, "eigenvector centrality": 0.023570432357043238, - "burt's constraint weighted": 0.32256502023401795, - "burt's constraint unweighted": 0.2975522821503287, + "burt's constraint weighted": 0.3225650202340179, + "burt's constraint unweighted": 0.29755228215032875, "affiliation": "University of Pennsylvania | Wharton School of the University of Pennsylvania", "country": "United States", "articles": "What Holds Attention? Linguistic Drivers of Engagement | Style, content, and the success of ideas | Expression Modalities: How Speaking Versus Writing Shapes Word of Mouth | Wisdom from words: marketing insights from text", @@ -3027,8 +3027,8 @@ "betweenness": 9.210283939896319e-05, "closeness": 0.018081291093843394, "eigenvector centrality": 0.018081291093843394, - "burt's constraint weighted": 0.3945907943067035, - "burt's constraint unweighted": 0.3802734375000001, + "burt's constraint weighted": 0.3945907943067034, + "burt's constraint unweighted": 0.38027343750000003, "affiliation": "King's College London", "country": "United Kingdom", "articles": "Young People Under \u2018Finfluencer\u2019: The Rise of Financial Influencers on Instagram: An Abstract | \u201cDoes It Go Without Saying?\u201d Implication of Electronic Word of Mouth in Luxury Branding: An Abstract | Studying the Effects of Sponsorship Disclosure and Message Complexity on Consumers\u2019 Response Via Text Analysis: An Abstract", @@ -3044,7 +3044,7 @@ "closeness": 0.014890475018459267, "eigenvector centrality": 0.014890475018459267, "burt's constraint weighted": 0.5534102387511478, - 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Gustavson School of Business", "country": "Canada", @@ -15544,8 +15544,8 @@ "betweenness": 1.0994931336653802e-05, "closeness": 0.00936768149882904, "eigenvector centrality": 0.00936768149882904, - "burt's constraint weighted": 0.7198666666666667, - "burt's constraint unweighted": 0.7044270833333333, + "burt's constraint weighted": 0.7198666666666668, + "burt's constraint unweighted": 0.7044270833333334, "affiliation": "FLAME University | National Institute of Industrial Engineering", "country": "India", "articles": "A critical review of international print advertisements: evolutionary analysis, assessment and elucidations, from 1965 to 2020 | Industrial-buying research 1965-2015: review and analysis", @@ -15688,8 +15688,8 @@ "betweenness": 0.0007476553308924586, "closeness": 0.026346604215456672, "eigenvector centrality": 0.026346604215456672, - "burt's constraint weighted": 0.23933912407938385, - "burt's constraint unweighted": 0.23933912407938385, + "burt's constraint weighted": 0.2393391240793838, + "burt's constraint unweighted": 0.2393391240793838, "affiliation": "Iscte \u2013 Instituto Universit\u00e1rio de Lisboa", "country": "Portugal", "articles": "Is this the beginning of the end for retail websites? A professional perspective | Past, present, and future research on self-service merchandising: a co-word and text mining approach | Service quality in airport hotel chains through the lens of online reviewers | Unfolding the characteristics of incentivized online reviews", @@ -15894,8 +15894,8 @@ "betweenness": 0.0008576046442589966, "closeness": 0.04675003314038266, "eigenvector centrality": 0.04675003314038266, - "burt's constraint weighted": 0.30799660292240816, - "burt's constraint unweighted": 0.2910166436366213, + "burt's constraint weighted": 0.3079966029224081, + "burt's constraint unweighted": 0.29101664363662133, "affiliation": "Goizueta Business School", "country": "United States", "articles": "Capturing Marketing Information to Fuel Growth | Capturing changes in social media content: A multiple latent changepoint topic model | Uniting the Tribes: Using Text for Marketing Insight", @@ -17512,8 +17512,8 @@ "betweenness": 8.246198502490352e-05, "closeness": 0.020615496256225878, "eigenvector centrality": 0.020615496256225878, - "burt's constraint weighted": 0.5780834467120183, - "burt's constraint unweighted": 0.5662977430555555, + "burt's constraint weighted": 0.5780834467120181, + "burt's constraint unweighted": 0.5662977430555556, "affiliation": "Saginaw Valley State University", "country": "United States", "articles": "Examining Country Image in Expert Electronic Word-of-Mouth: An Abstract | Nation Brands in Expert Electronic Word-of-Mouth: An Abstract", @@ -18073,7 +18073,7 @@ "closeness": 0.055679814751466994, "eigenvector centrality": 0.055679814751466994, "burt's constraint weighted": 0.18013944643358626, - "burt's constraint unweighted": 0.17095499951282597, + "burt's constraint unweighted": 0.170954999512826, "affiliation": "University of Melbourne | University of Surrey", "country": "Australia | United Kingdom", "articles": "Uniting the Tribes: Using Text for Marketing Insight | What Happens in Vegas Stays on TripAdvisor? A Theory and Technique to Understand Narrativity in Consumer Reviews | Detecting, preventing, and mitigating online firestorms in brand communities | Cutting through Content Clutter: How speech and image acts drive consumer sharing of social media brand messages", @@ -18088,7 +18088,7 @@ "betweenness": 0.0, "closeness": 0.04546333498055562, "eigenvector centrality": 0.04546333498055562, - "burt's constraint weighted": 0.41261732862821954, + "burt's constraint weighted": 0.4126173286282194, "burt's constraint unweighted": 0.40970379818594105, "articles": "Uniting the Tribes: Using Text for Marketing Insight", "journals": "Journal of Marketing", @@ -18226,7 +18226,7 @@ "betweenness": 0.0014183461424283404, "closeness": 0.03643752583000413, "eigenvector centrality": 0.03643752583000413, - "burt's constraint weighted": 0.4697238658777121, + "burt's constraint weighted": 0.46972386587771214, "burt's constraint unweighted": 0.4702777777777779, "articles": "When Words Sweat: Identifying Signals for Loan Default in the Text of Loan Applications | Extracting Features of Entertainment Products: A Guided Latent Dirichlet Allocation Approach Informed by the Psychology of Media Consumption", "journals": "Journal of Marketing Research", @@ -18623,7 +18623,7 @@ "closeness": 0.038414755913802806, "eigenvector centrality": 0.038414755913802806, "burt's constraint weighted": 0.6322141056858472, - "burt's constraint unweighted": 0.6343557098765432, + "burt's constraint unweighted": 0.6343557098765431, "affiliation": "Owen Graduate School of Management", "country": "United States", "articles": "What Happens in Vegas Stays on TripAdvisor? 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How expected and actual nutritional value affect the content and linguistic characteristics of online reviews for food products | Perception and gaze of diaspora: Analysis of affective, cognitive, & cultural factors in tourism", @@ -2211,8 +2211,8 @@ "betweenness": 0.0, "closeness": 0.010713832889565107, "eigenvector centrality": 0.010713832889565107, - "burt's constraint weighted": 0.7928949357520785, - "burt's constraint unweighted": 0.7928949357520785, + "burt's constraint weighted": 0.7928949357520786, + "burt's constraint unweighted": 0.7928949357520786, "affiliation": "Duquesne University", "country": "United States", "articles": "But it was supposed to be healthy! 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How expected and actual nutritional value affect the content and linguistic characteristics of online reviews for food products | Perception and gaze of diaspora: Analysis of affective, cognitive, & cultural factors in tourism", @@ -2211,8 +2211,8 @@ "betweenness": 0.0, "closeness": 0.010713832889565107, "eigenvector centrality": 0.010713832889565107, - "burt's constraint weighted": 0.7928949357520785, - "burt's constraint unweighted": 0.7928949357520785, + "burt's constraint weighted": 0.7928949357520786, + "burt's constraint unweighted": 0.7928949357520786, "affiliation": "Duquesne University", "country": "United States", "articles": "But it was supposed to be healthy! How expected and actual nutritional value affect the content and linguistic characteristics of online reviews for food products", @@ -2573,8 +2573,8 @@ "betweenness": 0.0, "closeness": 0.007471607890017932, "eigenvector centrality": 0.007471607890017932, - "burt's constraint weighted": 0.8311111111111109, - "burt's constraint unweighted": 0.8311111111111109, + "burt's constraint weighted": 0.831111111111111, + "burt's constraint unweighted": 0.831111111111111, "affiliation": "David Eccles School of Business", "country": "United States", "articles": "Algorithms propagate gender bias in the marketplace\u2014with consumers\u2019 cooperation", @@ -2765,8 +2765,8 @@ "betweenness": 0.00019297737778830383, "closeness": 0.023570432357043238, "eigenvector centrality": 0.023570432357043238, - "burt's constraint weighted": 0.32256502023401795, - "burt's constraint unweighted": 0.2975522821503287, + "burt's constraint weighted": 0.3225650202340179, + "burt's constraint unweighted": 0.29755228215032875, "affiliation": "University of Pennsylvania | Wharton School of the University of Pennsylvania", "country": "United States", "articles": "What Holds Attention? Linguistic Drivers of Engagement | Style, content, and the success of ideas | Expression Modalities: How Speaking Versus Writing Shapes Word of Mouth | Wisdom from words: marketing insights from text", @@ -3027,8 +3027,8 @@ "betweenness": 9.210283939896319e-05, "closeness": 0.018081291093843394, "eigenvector centrality": 0.018081291093843394, - "burt's constraint weighted": 0.3945907943067035, - "burt's constraint unweighted": 0.3802734375000001, + "burt's constraint weighted": 0.3945907943067034, + "burt's constraint unweighted": 0.38027343750000003, "affiliation": "King's College London", "country": "United Kingdom", "articles": "Young People Under \u2018Finfluencer\u2019: The Rise of Financial Influencers on Instagram: An Abstract | \u201cDoes It Go Without Saying?\u201d Implication of Electronic Word of Mouth in Luxury Branding: An Abstract | Studying the Effects of Sponsorship Disclosure and Message Complexity on Consumers\u2019 Response Via Text Analysis: An Abstract", @@ -3044,7 +3044,7 @@ "closeness": 0.014890475018459267, "eigenvector centrality": 0.014890475018459267, "burt's constraint weighted": 0.5534102387511478, - 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Gustavson School of Business", "country": "Canada", @@ -15544,8 +15544,8 @@ "betweenness": 1.0994931336653802e-05, "closeness": 0.00936768149882904, "eigenvector centrality": 0.00936768149882904, - "burt's constraint weighted": 0.7198666666666667, - "burt's constraint unweighted": 0.7044270833333333, + "burt's constraint weighted": 0.7198666666666668, + "burt's constraint unweighted": 0.7044270833333334, "affiliation": "FLAME University | National Institute of Industrial Engineering", "country": "India", "articles": "A critical review of international print advertisements: evolutionary analysis, assessment and elucidations, from 1965 to 2020 | Industrial-buying research 1965-2015: review and analysis", @@ -15688,8 +15688,8 @@ "betweenness": 0.0007476553308924586, "closeness": 0.026346604215456672, "eigenvector centrality": 0.026346604215456672, - "burt's constraint weighted": 0.23933912407938385, - "burt's constraint unweighted": 0.23933912407938385, + "burt's constraint weighted": 0.2393391240793838, + "burt's constraint unweighted": 0.2393391240793838, "affiliation": "Iscte \u2013 Instituto Universit\u00e1rio de Lisboa", "country": "Portugal", "articles": "Is this the beginning of the end for retail websites? A professional perspective | Past, present, and future research on self-service merchandising: a co-word and text mining approach | Service quality in airport hotel chains through the lens of online reviewers | Unfolding the characteristics of incentivized online reviews", @@ -15894,8 +15894,8 @@ "betweenness": 0.0008576046442589966, "closeness": 0.04675003314038266, "eigenvector centrality": 0.04675003314038266, - "burt's constraint weighted": 0.30799660292240816, - "burt's constraint unweighted": 0.2910166436366213, + "burt's constraint weighted": 0.3079966029224081, + "burt's constraint unweighted": 0.29101664363662133, "affiliation": "Goizueta Business School", "country": "United States", "articles": "Capturing Marketing Information to Fuel Growth | Capturing changes in social media content: A multiple latent changepoint topic model | Uniting the Tribes: Using Text for Marketing Insight", @@ -17512,8 +17512,8 @@ "betweenness": 8.246198502490352e-05, "closeness": 0.020615496256225878, "eigenvector centrality": 0.020615496256225878, - "burt's constraint weighted": 0.5780834467120183, - "burt's constraint unweighted": 0.5662977430555555, + "burt's constraint weighted": 0.5780834467120181, + "burt's constraint unweighted": 0.5662977430555556, "affiliation": "Saginaw Valley State University", "country": "United States", "articles": "Examining Country Image in Expert Electronic Word-of-Mouth: An Abstract | Nation Brands in Expert Electronic Word-of-Mouth: An Abstract", @@ -18073,7 +18073,7 @@ "closeness": 0.055679814751466994, "eigenvector centrality": 0.055679814751466994, "burt's constraint weighted": 0.18013944643358626, - "burt's constraint unweighted": 0.17095499951282597, + "burt's constraint unweighted": 0.170954999512826, "affiliation": "University of Melbourne | University of Surrey", "country": "Australia | United Kingdom", "articles": "Uniting the Tribes: Using Text for Marketing Insight | What Happens in Vegas Stays on TripAdvisor? A Theory and Technique to Understand Narrativity in Consumer Reviews | Detecting, preventing, and mitigating online firestorms in brand communities | Cutting through Content Clutter: How speech and image acts drive consumer sharing of social media brand messages", @@ -18088,7 +18088,7 @@ "betweenness": 0.0, "closeness": 0.04546333498055562, "eigenvector centrality": 0.04546333498055562, - "burt's constraint weighted": 0.41261732862821954, + "burt's constraint weighted": 0.4126173286282194, "burt's constraint unweighted": 0.40970379818594105, "articles": "Uniting the Tribes: Using Text for Marketing Insight", "journals": "Journal of Marketing", @@ -18226,7 +18226,7 @@ "betweenness": 0.0014183461424283404, "closeness": 0.03643752583000413, "eigenvector centrality": 0.03643752583000413, - "burt's constraint weighted": 0.4697238658777121, + "burt's constraint weighted": 0.46972386587771214, "burt's constraint unweighted": 0.4702777777777779, "articles": "When Words Sweat: Identifying Signals for Loan Default in the Text of Loan Applications | Extracting Features of Entertainment Products: A Guided Latent Dirichlet Allocation Approach Informed by the Psychology of Media Consumption", "journals": "Journal of Marketing Research", @@ -18623,7 +18623,7 @@ "closeness": 0.038414755913802806, "eigenvector centrality": 0.038414755913802806, "burt's constraint weighted": 0.6322141056858472, - "burt's constraint unweighted": 0.6343557098765432, + "burt's constraint unweighted": 0.6343557098765431, "affiliation": "Owen Graduate School of Management", "country": "United States", "articles": "What Happens in Vegas Stays on TripAdvisor? A Theory and Technique to Understand Narrativity in Consumer Reviews", @@ -18936,7 +18936,7 @@ "betweenness": 0.0, "closeness": 0.03782827109069131, "eigenvector centrality": 0.03782827109069131, - "burt's constraint weighted": 0.6009537597718826, + "burt's constraint weighted": 0.6009537597718827, "burt's constraint unweighted": 0.575927734375, "affiliation": "University of St. Gallen", "country": "Switzerland", @@ -19064,8 +19064,8 @@ "betweenness": 0.0, "closeness": 0.01881900301104048, "eigenvector centrality": 0.01881900301104048, - "burt's constraint weighted": 0.6366426582876799, - "burt's constraint unweighted": 0.6366426582876799, + "burt's constraint weighted": 0.6366426582876797, + "burt's constraint unweighted": 0.6366426582876797, "affiliation": "Iscte \u2013 Instituto Universit\u00e1rio de Lisboa", "country": "Portugal", "articles": "Unfolding the characteristics of incentivized online reviews", @@ -19080,7 +19080,7 @@ "betweenness": 0.0004672845818077866, "closeness": 0.022910090622136236, "eigenvector centrality": 0.022910090622136236, - 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"burt's constraint weighted": 0.3150571635861856, + "burt's constraint weighted": 0.3150571635861855, "burt's constraint unweighted": 0.30300878099173545, "affiliation": "The University of Texas at Austin", "country": "United States", @@ -19250,7 +19250,7 @@ "betweenness": 3.29847940099614e-05, "closeness": 0.02810304449648712, "eigenvector centrality": 0.02810304449648712, - "burt's constraint weighted": 0.3150571635861856, + "burt's constraint weighted": 0.3150571635861855, "burt's constraint unweighted": 0.30300878099173545, "affiliation": "The University of Texas at Austin", "country": "United States", @@ -19282,8 +19282,8 @@ "betweenness": 0.0, "closeness": 0.025941271842911187, "eigenvector centrality": 0.025941271842911187, - "burt's constraint weighted": 0.3269055726928433, - "burt's constraint unweighted": 0.3241980283678255, + "burt's constraint weighted": 0.32690557269284326, + "burt's constraint unweighted": 0.3241980283678256, "affiliation": "The University of Texas at Austin", "country": "United States", "articles": "Special Session: An Abstract on \u201cMarketing Techniques to Assist Public Sectors in Engaging Customers to Meet Societal and Individual Disasters Crisis Need and Beyond\u201d", @@ -19314,7 +19314,7 @@ "betweenness": 0.0, "closeness": 0.025941271842911187, "eigenvector centrality": 0.025941271842911187, - "burt's constraint weighted": 0.3269055726928433, + "burt's constraint weighted": 0.32690557269284326, "burt's constraint unweighted": 0.3241980283678256, "affiliation": "University of Central Florida", "country": "United States", @@ -19330,8 +19330,8 @@ "betweenness": 0.0, "closeness": 0.025941271842911187, "eigenvector centrality": 0.025941271842911187, - "burt's constraint weighted": 0.3269055726928433, - "burt's constraint unweighted": 0.32419802836782563, + "burt's constraint weighted": 0.32690557269284326, + "burt's constraint unweighted": 0.3241980283678256, "affiliation": "GENERAL LAND OFFICE, TEXAS", "country": "United States", "articles": "Special Session: An Abstract on \u201cMarketing Techniques to Assist Public Sectors in Engaging Customers to Meet Societal and Individual Disasters Crisis Need and Beyond\u201d", @@ -19346,7 +19346,7 @@ "betweenness": 0.0, "closeness": 0.025941271842911187, "eigenvector centrality": 0.025941271842911187, - "burt's constraint weighted": 0.3269055726928433, + "burt's constraint weighted": 0.32690557269284326, "burt's constraint unweighted": 0.3241980283678256, "affiliation": "GENERAL LAND OFFICE, TEXAS", "country": "United States", @@ -19378,8 +19378,8 @@ "betweenness": 0.0, "closeness": 0.025941271842911187, "eigenvector centrality": 0.025941271842911187, - "burt's constraint weighted": 0.3269055726928433, - "burt's constraint unweighted": 0.32419802836782563, + "burt's constraint weighted": 0.32690557269284326, + "burt's constraint unweighted": 0.3241980283678256, "affiliation": "GENERAL LAND OFFICE, TEXAS", "country": "United States", "articles": "Special Session: An Abstract on \u201cMarketing Techniques to Assist Public Sectors in Engaging Customers to Meet Societal and Individual Disasters Crisis Need and Beyond\u201d", @@ -19394,8 +19394,8 @@ "betweenness": 0.0, "closeness": 0.025941271842911187, "eigenvector centrality": 0.025941271842911187, - "burt's constraint weighted": 0.3269055726928433, - "burt's constraint unweighted": 0.3241980283678255, + "burt's constraint weighted": 0.32690557269284326, + "burt's constraint unweighted": 0.3241980283678256, "affiliation": "Que Advisors", "country": "Mexico", "articles": "Special Session: An Abstract on \u201cMarketing Techniques to Assist Public Sectors in Engaging Customers to Meet Societal and Individual Disasters Crisis Need and Beyond\u201d", @@ -19411,7 +19411,7 @@ "closeness": 0.025941271842911187, "eigenvector centrality": 0.025941271842911187, "burt's constraint weighted": 0.3269055726928433, - "burt's constraint unweighted": 0.32419802836782563, + "burt's constraint unweighted": 0.3241980283678256, "affiliation": "The University of Texas at Austin", "country": "United States", "articles": "Special Session: An Abstract on \u201cMarketing Techniques to Assist Public Sectors in Engaging Customers to Meet Societal and Individual Disasters Crisis Need and Beyond\u201d", @@ -25516,10 +25516,10 @@ "start_layout_for_seconds": 3.0, "sync_key": null, "sync_targets": [ - "selection", - "camera", + "layout", "hover", - "layout" + "selection", + "camera" ], "ui_settings": { "hideInfoPanel": false, @@ -25621,7 +25621,7 @@ } } }, - "c51bd8f52fe24759b5ecfd7256dee688": { + "5f74e72082db4cb6a4090d6327250bf6": { "model_name": "SigmaModel", "model_module": "ipysigma", "model_module_version": "^0.24.2", @@ -25898,8 +25898,8 @@ "betweenness": 0.00028485970659450214, "closeness": 0.058823529411764705, "eigenvector centrality": 0.058823529411764705, - "burt's constraint weighted": 0.5170833333333332, - 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"selection", - "camera", + "layout", "hover", - "layout" + "selection", + "camera" ], "ui_settings": { "hideInfoPanel": false, @@ -28803,7 +28803,7 @@ } } }, - "b522c943ff0d48588d4bc1b38dfb69ea": { + "3e52f5c58fa44b309e5cb401c0579342": { "model_name": "SigmaModel", "model_module": "ipysigma", "model_module_version": "^0.24.2", @@ -30086,10 +30086,10 @@ "start_layout_for_seconds": 3.0, "sync_key": null, "sync_targets": [ - "selection", - "camera", + "layout", "hover", - "layout" + "selection", + "camera" ], "ui_settings": { "hideInfoPanel": false, @@ -30195,7 +30195,7 @@ } diff --git a/networks/authors/network_2022_2023_louvain_pyvis.html b/networks/authors/network_2022_2023_louvain_pyvis.html index 05f8c4d..c5078c7 100644 --- a/networks/authors/network_2022_2023_louvain_pyvis.html +++ b/networks/authors/network_2022_2023_louvain_pyvis.html @@ -360,7 +360,7 @@

// parsing and collecting nodes and edges from the python - nodes = new vis.DataSet([{"affiliation": "UC Davis Graduate School of Management", "betweenness": 0.0, "centrality": 0.006276150627615062, "citations": 0, "closeness": 0.006276150627615063, "constraint": 0.925925925925926, "country": "United States", "font": {"color": "black"}, "group": 0, "id": "Loupos P.", "journal": "Marketing Letters", "label": "Loupos P.", "shape": "dot", "size": 6, "title": "What reviews foretell about opening weekend box office revenue: the harbinger of failure effect in the movie industry"}, {"affiliation": "UC Davis Graduate School of Management", "betweenness": 0.0, "centrality": 0.006276150627615062, "citations": 0, "closeness": 0.006276150627615063, "constraint": 0.925925925925926, "country": "United States", "font": {"color": "black"}, "group": 0, "id": "Peng Y.", "journal": "Marketing Letters", "label": "Peng Y.", "shape": "dot", "size": 6, "title": "What reviews foretell about opening weekend box office revenue: the harbinger of failure effect in the movie industry"}, {"affiliation": "UC Davis Graduate School of Management", "betweenness": 0.0, "centrality": 0.006276150627615062, "citations": 0, "closeness": 0.006276150627615063, "constraint": 0.925925925925926, "country": "United States", "font": {"color": "black"}, "group": 0, "id": "Li S.", "journal": "Marketing Letters", "label": "Li S.", "shape": "dot", "size": 6, "title": "What reviews foretell about opening weekend box office revenue: the harbinger of failure effect in the movie industry"}, {"affiliation": "UC Davis Graduate School of Management", "betweenness": 0.0, "centrality": 0.006276150627615062, "citations": 0, "closeness": 0.006276150627615063, "constraint": 0.925925925925926, "country": "United States", "font": {"color": "black"}, "group": 0, "id": "Hao H.", "journal": "Marketing Letters", "label": "Hao H.", "shape": "dot", "size": 6, "title": "What reviews foretell about opening weekend box office revenue: the harbinger of failure effect in the movie industry"}, {"affiliation": "Erasmus Universiteit Rotterdam", "betweenness": 0.0, "centrality": 0.0020920502092050207, "citations": 3, "closeness": 0.0020920502092050207, "constraint": 1.0, "country": "Netherlands", "font": {"color": "black"}, "group": 1, "id": "Krefeld-Schwalb A.", "journal": "Marketing Letters", "label": "Krefeld-Schwalb A.", "shape": "dot", "size": 2, "title": "Tighter nets for smaller fishes? Mapping the development of statistical practices in consumer research between 2008 and 2020"}, {"affiliation": "Karlsruher Institut f\u00fcr Technologie", "betweenness": 0.0, "centrality": 0.0020920502092050207, "citations": 3, "closeness": 0.0020920502092050207, "constraint": 1.0, "country": "Germany", "font": {"color": "black"}, "group": 1, "id": "Scheibehenne B.", "journal": "Marketing Letters", "label": "Scheibehenne B.", "shape": "dot", "size": 2, "title": "Tighter nets for smaller fishes? Mapping the development of statistical practices in consumer research between 2008 and 2020"}, {"affiliation": "EDHEC Business School", "betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.004707112970711297, "constraint": 1.0069444444444444, "country": "France", "font": {"color": "black"}, "group": 2, "id": "Gordeliy I.", "journal": "Journal of Consumer Research", "label": "Gordeliy I.", "shape": "dot", "size": 4, "title": "Been There, Done That: How Episodic and Semantic Memory Affects the Language of Authentic and Fictitious Reviews"}, {"affiliation": "University of Massachusetts Lowell", "betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.004707112970711297, "constraint": 1.0069444444444444, "country": "United States", "font": {"color": "black"}, "group": 2, "id": "Kronrod A.", "journal": "Journal of Consumer Research", "label": "Kronrod A.", "shape": "dot", "size": 4, "title": "Been There, Done That: How Episodic and Semantic Memory Affects the Language of Authentic and Fictitious Reviews"}, {"affiliation": "American University | Kogod School of Business", "betweenness": 1.7543397980754893e-05, "centrality": 0.006276150627615062, "citations": 3, "closeness": 0.006276150627615063, "constraint": 0.6111111111111112, "country": "United States", "font": {"color": "black"}, "group": 2, "id": "Lee J.k.", "journal": "Journal of Consumer Research", "label": "Lee J.k.", "shape": "dot", "size": 6, "title": "Been There, Done That: How Episodic and Semantic Memory Affects the Language of Authentic and Fictitious Reviews | Influencer-Generated Reference Groups"}, {"affiliation": "NYU Shanghai", "betweenness": 0.0, "centrality": 0.0020920502092050207, "citations": 3, "closeness": 0.0037656903765690376, "constraint": 1.0, "country": "China", "font": {"color": "black"}, "group": 2, "id": "Junque De Fortuny E.", "journal": "Journal of Consumer Research", "label": "Junque De Fortuny E.", "shape": "dot", "size": 2, "title": "Influencer-Generated Reference Groups"}, {"betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.0041841004184100415, "constraint": 1.125, "font": {"color": "black"}, "group": 3, "id": "Chang H.H.", "journal": "Journal of Marketing Research", "label": "Chang H.H.", "shape": "dot", "size": 4, "title": "More Voices Persuade: The Attentional Benefits of Voice Numerosity"}, {"betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.0041841004184100415, "constraint": 1.125, "font": {"color": "black"}, "group": 3, "id": "Mukherjee A.", "journal": "Journal of Marketing Research", "label": "Mukherjee A.", "shape": "dot", "size": 4, "title": "More Voices Persuade: The Attentional Benefits of Voice Numerosity"}, {"betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.0041841004184100415, "constraint": 1.125, "font": {"color": "black"}, "group": 3, "id": "Chattopadhyay A.", "journal": "Journal of Marketing Research", "label": "Chattopadhyay A.", "shape": "dot", "size": 4, "title": "More Voices Persuade: The Attentional Benefits of Voice Numerosity"}, {"affiliation": "Izmir Ekonomi Universitesi", "betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.0041841004184100415, "constraint": 1.125, "country": "Turkey", "font": {"color": "black"}, "group": 4, "id": "Dobrucal\u0131 Yelkenci B.", "journal": "Marketing Intelligence and Planning", "label": "Dobrucal\u0131 Yelkenci B.", "shape": "dot", "size": 4, "title": "Online complaint handling: a\u00a0text\u00a0analytics-based classification framework"}, {"affiliation": "Dokuz Eyl\u00fcl \u00dcniversitesi", "betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.0041841004184100415, "constraint": 1.125, "country": "Turkey", "font": {"color": "black"}, "group": 4, "id": "\u00d6zda\u011fo\u011flu G.", "journal": "Marketing Intelligence and Planning", "label": "\u00d6zda\u011fo\u011flu G.", "shape": "dot", "size": 4, "title": "Online complaint handling: a\u00a0text\u00a0analytics-based classification framework"}, {"affiliation": "Dokuz Eyl\u00fcl \u00dcniversitesi", "betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.0041841004184100415, "constraint": 1.125, "country": "Turkey", "font": {"color": "black"}, "group": 4, "id": "\u0130lter B.", "journal": "Marketing Intelligence and Planning", "label": "\u0130lter B.", "shape": "dot", "size": 4, "title": "Online complaint handling: a\u00a0text\u00a0analytics-based classification framework"}, {"affiliation": "Indian Institute of Management Ranchi", "betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.005578800557880055, "constraint": 0.953125, "country": "India", "font": {"color": "black"}, "group": 5, "id": "Chakraborty S.", "journal": "Journal of Retailing and Consumer Services", "label": "Chakraborty S.", "shape": "dot", "size": 4, "title": "Text mining approach to explore determinants of grocery mobile app satisfaction using online customer reviews"}, {"affiliation": "Indian Institute of Management Ranchi", "betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 0, "closeness": 0.005578800557880055, "constraint": 0.953125, "country": "India", "font": {"color": "black"}, "group": 5, "id": "Kumar A.", "journal": "Journal of Retailing and Consumer Services", "label": "Kumar A.", "shape": "dot", "size": 4, "title": "Text mining approach to explore determinants of grocery mobile app satisfaction using online customer reviews"}, {"affiliation": "Indian Institute of Management Ranchi", "betweenness": 3.5086795961509786e-05, "centrality": 0.008368200836820083, "citations": 1, "closeness": 0.008368200836820083, "constraint": 0.6024305555555556, "country": "India", "font": {"color": "black"}, "group": 5, "id": "Bala P.K.", "journal": "Journal of Retailing and Consumer Services | Journal of Hospitality Marketing and Management", "label": "Bala P.K.", "shape": "dot", "size": 8, "title": "Text mining approach to explore determinants of grocery mobile app satisfaction using online customer reviews | What affects the use of green technology in hotels? Assessing hotel management viewpoint using natural language processing based qualitative study"}, {"affiliation": "Indian Institute of Management Ranchi | International Management Institute, Kolkata", "betweenness": 0.0, "centrality": 0.008368200836820083, "citations": 2, "closeness": 0.005578800557880055, "constraint": 1.134259259259259, "country": "India", "font": {"color": "black"}, "group": 5, "id": "Ray A.", "journal": "Journal of Hospitality Marketing and Management", "label": "Ray A.", "shape": "dot", "size": 8, "title": "What affects the use of green technology in hotels? Assessing hotel management viewpoint using natural language processing based qualitative study"}, {"affiliation": "College of Business and Economics", "betweenness": 0.0, "centrality": 0.0041841004184100415, "citations": 1, "closeness": 0.005578800557880055, "constraint": 1.0711805555555554, "country": "Qatar", "font": {"color": "black"}, "group": 5, "id": "Rana N.P.", "journal": "Journal of Hospitality Marketing and Management", "label": "Rana N.P.", "shape": "dot", "size": 4, "title": "What affects the use of green technology in hotels? Assessing hotel management viewpoint using natural language processing based qualitative study"}, {"affiliation": "Qatar University", "betweenness": 0.0, "centrality": 0.010460251046025104, "citations": 0, "closeness": 0.010460251046025104, "constraint": 0.6480000000000001, "country": "Qatar", "font": {"color": "black"}, "group": 6, "id": "Abumalloh R.A.", "journal": "Journal of Retailing and Consumer Services", "label": "Abumalloh R.A.", "shape": "dot", "size": 10, "title": "Analysis of customers\u0027 satisfaction with baby products: The moderating role of brand image"}, {"affiliation": "UCSI University", "betweenness": 0.0, "centrality": 0.010460251046025104, "citations": 0, "closeness": 0.010460251046025104, "constraint": 0.6480000000000001, "country": "Malaysia", "font": {"color": "black"}, "group": 6, "id": "Nilashi M.", "journal": "Journal of Retailing and Consumer Services", "label": "Nilashi M.", "shape": "dot", "size": 10, "title": "Analysis of customers\u0027 satisfaction with baby products: The moderating role of brand image"}, {"affiliation": "Princess Nourah Bint Abdulrahman University", "betweenness": 0.0, "centrality": 0.010460251046025104, "citations": 0, "closeness": 0.010460251046025104, "constraint": 0.6480000000000001, "country": "Saudi Arabia", "font": {"color": "black"}, "group": 6, "id": "Samad S.", "journal": "Journal of Retailing and Consumer Services", "label": "Samad S.", "shape": "dot", "size": 10, "title": "Analysis of customers\u0027 satisfaction with baby products: The moderating role of brand image"}, {"affiliation": "Najran University", "betweenness": 0.0, "centrality": 0.010460251046025104, "citations": 0, "closeness": 0.010460251046025104, "constraint": 0.6480000000000001, "country": "Saudi Arabia", "font": {"color": "black"}, "group": 6, "id": "Alrizq M.", "journal": "Journal of Retailing and Consumer Services", "label": "Alrizq M.", "shape": "dot", "size": 10, "title": "Analysis of customers\u0027 satisfaction with baby products: The moderating role of brand image"}, {"affiliation": "Najran University", "betweenness": 0.0, "centrality": 0.010460251046025104, "citations": 0, "closeness": 0.010460251046025104, "constraint": 0.6480000000000001, "country": "Saudi Arabia", "font": {"color": "black"}, "group": 6, "id": "Alyami S.", "journal": "Journal of Retailing and Consumer Services", "label": "Alyami S.", "shape": "dot", "size": 10, "title": "Analysis of customers\u0027 satisfaction with baby products: The moderating role of brand image"}, {"affiliation": "Najran University", "betweenness": 0.0, "centrality": 0.010460251046025104, "citations": 0, "closeness": 0.010460251046025104, "constraint": 0.6480000000000001, "country": "Saudi Arabia", "font": {"color": "black"}, "group": 6, "id": "Alghamdi A.", "journal": "Journal of Retailing and Consumer Services", "label": "Alghamdi A.", "shape": "dot", "size": 10, "title": "Analysis of customers\u0027 satisfaction with baby products: The moderating role of 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Transforming customer experience with digital voice assistants", "sourcetitle": "Technological Forecasting and Social Change", @@ -30652,7 +457,7 @@ } }, { - "key": "85105848947", + "key": 85105848947, "attributes": { "title": "Online Reviews on Online Travel Agency: Understanding Tourists\u2019 Perceived Attributes of Taipei\u2019s Economy Hotels", "sourcetitle": "Journal of Quality Assurance in Hospitality and Tourism", @@ -30670,13 +475,8 @@ } }, { - "key": "85150347354", + "key": 85150347354, "attributes": { - "title": "How online reviews with different influencing factors affect the diffusion of new products", - "sourcetitle": "International Journal of Consumer Studies", - "author": "Sun B.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.02095238095238095, "betweenness": 0.0, "closeness": 0.0, @@ -30687,7 +487,7 @@ } }, { - "key": "85143325015", + "key": 85143325015, "attributes": { "title": "Preference Characteristics on Consumers' Online Consumption of Fresh Agricultural Products under the Outbreak of COVID-19: An Analysis of Online Review Data Based on LDA Model", "sourcetitle": "Procedia Computer Science", @@ -30705,7 +505,7 @@ } }, { - "key": "85119666609", + "key": 85119666609, "attributes": { "title": "Factors correlated with the perceived usefulness of online reviews for consumers: a meta-analysis of the moderating effects of product type", "sourcetitle": "Aslib Journal of Information Management", @@ -30723,7 +523,7 @@ } }, { - "key": "85133088523", + "key": 85133088523, "attributes": { "title": "JD.com: Operations Research Algorithms Drive Intelligent Warehouse Robots to Work", "sourcetitle": "Interfaces", @@ -30741,7 +541,7 @@ } }, { - "key": "85137084948", + "key": 85137084948, "attributes": { "title": "Comprehensive helpfulness of online reviews: A dynamic strategy for ranking reviews by intrinsic and extrinsic helpfulness", "sourcetitle": "Decision Support Systems", @@ -30759,7 +559,7 @@ } }, { - "key": "85107876579", + "key": 85107876579, "attributes": { "title": "Which social media posts generate the most buzz? Evidence from WeChat", "sourcetitle": "Internet Research", @@ -30777,7 +577,7 @@ } }, { - "key": "85110594941", + "key": 85110594941, "attributes": { "title": "Title redacted: the impact of negative online review censorship", "sourcetitle": "Journal of Product and Brand Management", @@ -30795,7 +595,7 @@ } }, { - "key": "85119498191", + "key": 85119498191, "attributes": { "title": "The impact of COVID-19 on online product reviews", "sourcetitle": "Journal of Product and Brand Management", @@ -30813,7 +613,7 @@ } }, { - "key": "85109090989", + "key": 85109090989, "attributes": { "title": "How guest-host interactions affect consumer experiences in the sharing economy: New evidence from a configurational analysis based on consumer reviews", "sourcetitle": "Decision Support Systems", @@ -30831,7 +631,7 @@ } }, { - "key": "85100150393", + "key": 85100150393, "attributes": { "title": "Online prejudice and barriers to digital innovation: Empirical investigations of Chinese consumers", "sourcetitle": "Information Systems Journal", @@ -30849,7 +649,7 @@ } }, { - "key": "85110635944", + "key": 85110635944, "attributes": { "title": "Understanding the interplay between online reviews and growth of independent and branded hotels", "sourcetitle": "Decision Support Systems", @@ -30867,13 +667,8 @@ } }, { - "key": "85149572870", + "key": 85149572870, "attributes": { - "title": "It is not just a name: Effects of proper name for high-quality versus low-quality brands", - "sourcetitle": "Psychology and Marketing", - "author": "Rathee S.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.011428571428571429, "betweenness": 0.0, "closeness": 0.0, @@ -30884,7 +679,7 @@ } }, { - "key": "85127389635", + "key": 85127389635, "attributes": { "title": "Corporate social responsibility and perceived fairness of price increases", "sourcetitle": "Psychology and Marketing", @@ -30902,7 +697,7 @@ } }, { - "key": "85122312472", + "key": 85122312472, "attributes": { "title": "Consumer reactions to pay-what-you-want and name-your-own-price mechanisms", "sourcetitle": "Journal of Consumer Behaviour", @@ -30920,7 +715,7 @@ } }, { - "key": "85118630556", + "key": 85118630556, "attributes": { "title": "Value added or overload? A study of the countervailing effects of non-core features on mobile banking apps", "sourcetitle": "Journal of Consumer Behaviour", @@ -30938,7 +733,7 @@ } }, { - "key": "85133916657", + "key": 85133916657, "attributes": { "title": "Mitigating implicit racial bias in tipping: when direct and indirect experience matters", "sourcetitle": "Journal of Consumer Marketing", @@ -30956,7 +751,7 @@ } }, { - "key": "85124531430", + "key": 85124531430, "attributes": { "title": "The role of original process in creating product essence and authenticity", "sourcetitle": "Journal of Consumer Psychology", @@ -30974,7 +769,7 @@ } }, { - "key": "85129452551", + "key": 85129452551, "attributes": { "title": "Brand logos versus brand names: A comparison of the memory effects of textual and pictorial brand elements placed in computer games", "sourcetitle": "Journal of Business Research", @@ -30992,7 +787,7 @@ } }, { - "key": "85132327378", + "key": 85132327378, "attributes": { "title": "Voice bots on the frontline: Voice-based interfaces enhance flow-like consumer experiences & boost service outcomes", "sourcetitle": "Journal of the Academy of Marketing Science", @@ -31010,7 +805,7 @@ } }, { - "key": "85120158867", + "key": 85120158867, "attributes": { "title": "Search modality effects: merely changing product search modality alters purchase intentions", "sourcetitle": "Journal of the Academy of Marketing Science", @@ -31028,7 +823,7 @@ } }, { - "key": "85120855035", + "key": 85120855035, "attributes": { "title": "Voice Assistant vs. Chatbot \u2013 Examining the Fit Between Conversational Agents\u2019 Interaction Modalities and Information Search Tasks", "sourcetitle": "Information Systems Frontiers", @@ -31046,7 +841,7 @@ } }, { - "key": "85115105686", + "key": 85115105686, "attributes": { "title": "What influences the purchase of virtual gifts in live streaming in China? A cultural context-sensitive model", "sourcetitle": "Information Systems Journal", @@ -31064,13 +859,8 @@ } }, { - "key": "85149566147", + "key": 85149566147, "attributes": { - "title": "Satisfaction dimensions influencing consumers\u2019 behavioral intentions through structural topic modeling analysis of restaurant reviews", - "sourcetitle": "Consumer Behavior in Tourism and Hospitality", - "author": "Burkov I.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.015238095238095238, "betweenness": 0.0, "closeness": 0.0, @@ -31081,7 +871,7 @@ } }, { - "key": "85123601413", + "key": 85123601413, "attributes": { "title": "Process vs. outcome: Effects of food photo types in online restaurant reviews on consumers\u2019 purchase intention", "sourcetitle": "International Journal of Hospitality Management", @@ -31099,7 +889,7 @@ } }, { - "key": "85100861404", + "key": 85100861404, "attributes": { "title": "Role of Emotions in Fine Dining Restaurant Online Reviews: The Applications of Semantic Network Analysis and a Machine Learning Algorithm", "sourcetitle": "International Journal of Hospitality and Tourism Administration", @@ -31117,7 +907,7 @@ } }, { - "key": "85146232194", + "key": 85146232194, "attributes": { "title": "Know your guests\u2019 preferences before they arrive at your hotel: evidence from TripAdvisor", "sourcetitle": "Consumer Behavior in Tourism and Hospitality", @@ -31135,7 +925,7 @@ } }, { - "key": "85117942592", + "key": 85117942592, "attributes": { "title": "An analysis of tripadvisor reviews of 127 urban rail transit networks worldwide", "sourcetitle": "Travel Behaviour and Society", @@ -31153,7 +943,7 @@ } }, { - "key": "85132843243", + "key": 85132843243, "attributes": { "title": "Online customer reviews: insights from the coffee shops industry and the moderating effect of business types", "sourcetitle": "Tourism Review", @@ -31171,7 +961,7 @@ } }, { - "key": "85123781663", + "key": 85123781663, "attributes": { "title": "Mining behavioural and sentiment-dependent linguistic patterns from restaurant reviews for fake review detection", "sourcetitle": "Technological Forecasting and Social Change", @@ -31189,7 +979,7 @@ } }, { - "key": "85099821122", + "key": 85099821122, "attributes": { "title": "Customer Online Feedback with an Identity Versus No Identity: The Influence on Review Comments", "sourcetitle": "Journal of Hospitality and Tourism Research", @@ -31207,7 +997,7 @@ } }, { - "key": "85120946578", + "key": 85120946578, "attributes": { "title": "Why am I satisfied? See my reviews \u2013 Price and location matter in the restaurant industry", "sourcetitle": "International Journal of Hospitality Management", @@ -31225,13 +1015,8 @@ } }, { - "key": "85146949978", + "key": 85146949978, "attributes": { - "title": "It is about inclusion! Mining online reviews to understand the needs of adaptive clothing customers", - "sourcetitle": "International Journal of Consumer Studies", - "author": "Li M.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.005714285714285714, "betweenness": 0.0, "closeness": 0.0, @@ -31242,7 +1027,7 @@ } }, { - "key": "85124378925", + "key": 85124378925, "attributes": { "title": "How to identify product defects and segment consumer groups on an online auto forum", "sourcetitle": "International Journal of Consumer Studies", @@ -31260,7 +1045,7 @@ } }, { - "key": "85100059556", + "key": 85100059556, "attributes": { "title": "Voluntary simplicity: An exploration through text analysis", "sourcetitle": "International Journal of Consumer Studies", @@ -31278,7 +1063,7 @@ } }, { - "key": "85129139306", + "key": 85129139306, "attributes": { "title": "Sentiment Analysis from User-Generated Reviews of Ride-Sharing Mobile Applications", "sourcetitle": "Proceedings - 6th International Conference on Computing Methodologies and Communication, ICCMC 2022", @@ -31296,13 +1081,8 @@ } }, { - "key": "85139387322", + "key": 85139387322, "attributes": { - "title": "Analysing customers' reviews and ratings for online food deliveries: A text mining approach", - "sourcetitle": "International Journal of Consumer Studies", - "author": "Khan F.M.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.007619047619047619, "betweenness": 0.0, "closeness": 0.0, @@ -31313,7 +1093,7 @@ } }, { - "key": "85128510282", + "key": 85128510282, "attributes": { "title": "Regaining partner trust in the food delivery business: case of Zomato", "sourcetitle": "Emerald Emerging Markets Case Studies", @@ -31331,7 +1111,7 @@ } }, { - "key": "85105052937", + "key": 85105052937, "attributes": { "title": "Crisis-induced behavior: From fear and frugality to the familiar", "sourcetitle": "International Journal of Consumer Studies", @@ -31349,7 +1129,7 @@ } }, { - "key": "85104658464", + "key": 85104658464, "attributes": { "title": "Food packaging during the COVID-19 pandemic: Consumer perceptions", "sourcetitle": "International Journal of Consumer Studies", @@ -31367,7 +1147,7 @@ } }, { - "key": "85105776686", + "key": 85105776686, "attributes": { "title": "Consumption practices during the COVID-19 crisis", "sourcetitle": "International Journal of Consumer Studies", @@ -31385,13 +1165,8 @@ } }, { - "key": "85138717027", + "key": 85138717027, "attributes": { - "title": "Examining post-purchase consumer responses to product automation", - "sourcetitle": "Journal of the Academy of Marketing Science", - "author": "Smith L.W.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.011428571428571429, "betweenness": 0.0, "closeness": 0.0, @@ -31402,7 +1177,7 @@ } }, { - "key": "85094879481", + "key": 85094879481, "attributes": { "title": "Artificial Intelligence in Utilitarian vs. Hedonic Contexts: The \u201cWord-of-Machine\u201d Effect", "sourcetitle": "Journal of Marketing", @@ -31420,7 +1195,7 @@ } }, { - "key": "85126859364", + "key": 85126859364, "attributes": { "title": "Trojan horse or useful helper? A relationship perspective on artificial intelligence assistants with humanlike features", "sourcetitle": "Journal of the Academy of Marketing Science", @@ -31438,7 +1213,7 @@ } }, { - "key": "85126885985", + "key": 85126885985, "attributes": { "title": "Technology devalues luxury? Exploring consumer responses to AI-designed luxury products", "sourcetitle": "Journal of the Academy of Marketing Science", @@ -31456,7 +1231,7 @@ } }, { - "key": "85120803598", + "key": 85120803598, "attributes": { "title": "Appropriate service robots in exchange and communal relationships", "sourcetitle": "Journal of Business Research", @@ -31474,7 +1249,7 @@ } }, { - "key": "85116068116", + "key": 85116068116, "attributes": { "title": "Effects of Payment on User Engagement in Online Courses", "sourcetitle": "Journal of Marketing Research", @@ -31492,7 +1267,7 @@ } }, { - "key": "85125535762", + "key": 85125535762, "attributes": { "title": "AI increases unethical consumer behavior due to reduced anticipatory guilt", "sourcetitle": "Journal of the Academy of Marketing Science", @@ -31510,13 +1285,8 @@ } }, { - "key": "85146998548", + "key": 85146998548, "attributes": { - "title": "Exploring mobile banking service quality dimensions in Pakistan: a\u00a0text mining approach", - "sourcetitle": "International Journal of Bank Marketing", - "author": "Hussain A.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.022857142857142857, "betweenness": 0.0, "closeness": 0.0, @@ -31527,7 +1297,7 @@ } }, { - "key": "85124529279", + "key": 85124529279, "attributes": { "title": "A fuzzy MCDM decision-making model for m-banking evaluations: comparing several m-banking applications", "sourcetitle": "Journal of Ambient Intelligence and Humanized Computing", @@ -31545,7 +1315,7 @@ } }, { - "key": "85123048094", + "key": 85123048094, "attributes": { "title": "A Comparative Study of Users versus Non-Users\u2019 Behavioral Intention towards M-Banking Apps\u2019 Adoption", "sourcetitle": "Information (Switzerland)", @@ -31563,7 +1333,7 @@ } }, { - "key": "85120993613", + "key": 85120993613, "attributes": { "title": "Examining consumer experience in using m-banking apps: A study of its antecedents and outcomes", "sourcetitle": "Journal of Retailing and Consumer Services", @@ -31581,7 +1351,7 @@ } }, { - "key": "85133254992", + "key": 85133254992, "attributes": { "title": "Advances in mobile financial services: a review of the literature and future research directions", "sourcetitle": "International Journal of Bank Marketing", @@ -31599,7 +1369,7 @@ } }, { - "key": "85106255440", + "key": 85106255440, "attributes": { "title": "Sustainable mobile banking application: a text mining approach to explore critical success factors", "sourcetitle": "Journal of Enterprise Information Management", @@ -31617,7 +1387,7 @@ } }, { - "key": "85115197498", + "key": 85115197498, "attributes": { "title": "The influences of technological characteristics and user beliefs on customers' perceptions of live chat usage in mobile banking", "sourcetitle": "International Journal of Bank Marketing", @@ -31635,7 +1405,7 @@ } }, { - "key": "85099438992", + "key": 85099438992, "attributes": { "title": "Adoption of mobile banking in rural China: Impact of information dissemination channel", "sourcetitle": "Socio-Economic Planning Sciences", @@ -31653,7 +1423,7 @@ } }, { - "key": "85120045665", + "key": 85120045665, "attributes": { "title": "Digital voice-of-customer processing by topic modelling algorithms: insights to validate empirical results", "sourcetitle": "International Journal of Quality and Reliability Management", @@ -31671,7 +1441,7 @@ } }, { - "key": "85096445019", + "key": 85096445019, "attributes": { "title": "Text Preprocessing for Text Mining in Organizational Research: Review and Recommendations", "sourcetitle": "Organizational Research Methods", @@ -31689,7 +1459,7 @@ } }, { - "key": "85133626698", + "key": 85133626698, "attributes": { "title": "Mobile banking service quality and customer value co-creation intention: a moderated mediated model", "sourcetitle": "International Journal of Bank Marketing", @@ -31707,7 +1477,7 @@ } }, { - "key": "85110845350", + "key": 85110845350, "attributes": { "title": "Are microtargeted campaign messages more negative and diverse? An analysis of Facebook Ads in European election campaigns", "sourcetitle": "European Political Science", @@ -31725,7 +1495,7 @@ } }, { - "key": "85131411625", + "key": 85131411625, "attributes": { "title": "Reputation and its consequences in Fintech services: the case of mobile banking", "sourcetitle": "International Journal of Bank Marketing", @@ -31743,7 +1513,7 @@ } }, { - "key": "85150498750", + "key": 85150498750, "attributes": { "title": "Paralanguage Classifier (PARA): An Algorithm for Automatic Coding of Paralinguistic Nonverbal Parts of Speech in Text", "sourcetitle": "Journal of Marketing Research", @@ -31761,7 +1531,7 @@ } }, { - "key": "85128927549", + "key": 85128927549, "attributes": { "title": "The Power of Profanity: The Meaning and Impact of Swear Words in Word of Mouth", "sourcetitle": "Journal of Marketing Research", @@ -31779,7 +1549,7 @@ } }, { - "key": "85149071663", + "key": 85149071663, "attributes": { "title": "Expression Modalities: How Speaking Versus Writing Shapes Word of Mouth", "sourcetitle": "Journal of Consumer Research", @@ -31797,7 +1567,7 @@ } }, { - "key": "85122333187", + "key": 85122333187, "attributes": { "title": "Attribute Sentiment Scoring with Online Text Reviews: Accounting for Language Structure and Missing Attributes", "sourcetitle": "Journal of Marketing Research", @@ -31815,13 +1585,8 @@ } }, { - "key": "85126071763", + "key": 85126071763, "attributes": { - "title": "Systematic differences in online reviews of hotel services between business and leisure travelers", - "sourcetitle": "Journal of Vacation Marketing", - "author": "Kim J.M.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.0019047619047619048, "betweenness": 0.0, "closeness": 0.0, @@ -31832,7 +1597,7 @@ } }, { - "key": "85118501430", + "key": 85118501430, "attributes": { "title": "Which Marketer-generated-content is more effective? An experimental study in the context of a peer-to-peer accommodation platform", "sourcetitle": "International Journal of Hospitality Management", @@ -31850,13 +1615,8 @@ } }, { - "key": "85143761358", + "key": 85143761358, "attributes": { - "title": "Exploring mobile banking adoption and service quality features through user-generated content: the application of a topic modeling\u00a0approach to Google Play\u00a0Store reviews", - "sourcetitle": "International Journal of Bank Marketing", - "author": "\u00c7all\u0131 L.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.011428571428571429, "betweenness": 0.0, "closeness": 0.0, @@ -31867,7 +1627,7 @@ } }, { - "key": "85129655522", + "key": 85129655522, "attributes": { "title": "Role of social media on mobile banking adoption among consumers", "sourcetitle": "Technological Forecasting and Social Change", @@ -31885,7 +1645,7 @@ } }, { - "key": "85143788939", + "key": 85143788939, "attributes": { "title": "Understanding Airline Passengers during Covid-19 Outbreak to Improve Service Quality: Topic Modeling Approach to Complaints with Latent Dirichlet Allocation Algorithm", "sourcetitle": "Transportation Research Record", @@ -31903,7 +1663,7 @@ } }, { - "key": "85123478794", + "key": 85123478794, "attributes": { "title": "Exploring users' adoption intentions in the evolution of artificial intelligence mobile banking applications: the intelligent and anthropomorphic perspectives", "sourcetitle": "International Journal of Bank Marketing", @@ -31921,7 +1681,7 @@ } }, { - "key": "85130541928", + "key": 85130541928, "attributes": { "title": "What affects the online ratings of restaurant consumers: a research perspective on text-mining big data analysis", "sourcetitle": "International Journal of Contemporary Hospitality Management", @@ -31939,7 +1699,7 @@ } }, { - "key": "85135862502", + "key": 85135862502, "attributes": { "title": "Unraveling the relationship between the dimensions of user experience and user satisfaction: A smart speaker case", "sourcetitle": "Technology in Society", @@ -31957,7 +1717,7 @@ } }, { - "key": "85130973364", + "key": 85130973364, "attributes": { "title": "Consumer multihoming predisposition on food platforms: Does gender matter?", "sourcetitle": "Journal of Retailing and Consumer Services", @@ -31975,7 +1735,7 @@ } }, { - "key": "85129752919", + "key": 85129752919, "attributes": { "title": "Convenience stores in the digital age: A focus on the customer experience and revisit intentions", "sourcetitle": "Journal of Retailing and Consumer Services", @@ -31993,7 +1753,7 @@ } }, { - "key": "85124071610", + "key": 85124071610, "attributes": { "title": "\u201cI can get no e-satisfaction\u201d. What analytics say? Evidence using satisfaction data from e-commerce", "sourcetitle": "Journal of Retailing and Consumer Services", @@ -32011,7 +1771,7 @@ } }, { - "key": "85124305982", + "key": 85124305982, "attributes": { "title": "User quality of experience estimation using social network analysis", "sourcetitle": "Multimedia Systems", @@ -32029,7 +1789,7 @@ } }, { - "key": "85133658196", + "key": 85133658196, "attributes": { "title": "User Experience Quantification Model from Online User Reviews", "sourcetitle": "Applied Sciences (Switzerland)", @@ -32047,7 +1807,7 @@ } }, { - "key": "85133645256", + "key": 85133645256, "attributes": { "title": "Cluster-based analysis of COVID-19 cases using self-organizing map neural network and K-means methods to improve medical decision-making", "sourcetitle": "Informatics in Medicine Unlocked", @@ -32065,13 +1825,8 @@ } }, { - "key": "85142245402", + "key": 85142245402, "attributes": { - "title": "Complaint De-Escalation Strategies on Social Media", - "sourcetitle": "Journal of Marketing", - 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Evidence from the Video Game Industry", "sourcetitle": "Journal of Business Ethics", @@ -32580,7 +2305,7 @@ } }, { - "key": "85125890876", + "key": 85125890876, "attributes": { "title": "The queer manifesto: Imagining new possibilities and futures for marketing and consumer research", "sourcetitle": "Marketing Theory", @@ -32598,7 +2323,7 @@ } }, { - "key": "85133969619", + "key": 85133969619, "attributes": { "title": "Future needs in gender and LGBT advertising portrayals", "sourcetitle": "International Journal of Advertising", @@ -32616,7 +2341,7 @@ } }, { - "key": "85135874951", + "key": 85135874951, "attributes": { "title": "Conceptualizing brand purpose and considering its implications for consumer eudaimonic well-being", "sourcetitle": "Journal of Consumer Psychology", @@ -32634,7 +2359,7 @@ } }, { - "key": "85129188180", + "key": 85129188180, "attributes": { "title": "Finding gold at the end of the rainbowflag? Claim vagueness and presence of emotional imagery as factors to perceive rainbowwashing", "sourcetitle": "International Journal of Advertising", @@ -32652,7 +2377,7 @@ } }, { - "key": "85104828332", + "key": 85104828332, "attributes": { "title": "Evidence on the Economic Consequences of Marriage Equality and LGBT Human Rights", "sourcetitle": "Journal of Business Ethics", @@ -32670,7 +2395,7 @@ } }, { - "key": "85087360791", + "key": 85087360791, "attributes": { "title": "Coping and career choices: Irish gay men\u2019s passage from hopelessness to redemption", "sourcetitle": "Consumption Markets and Culture", @@ -32688,7 +2413,7 @@ } }, { - "key": "85102201243", + "key": 85102201243, "attributes": { "title": "Influence for social good: exploring the roles of influencer identity and comment section in Instagram-based LGBTQ-centric corporate social responsibility advertising", "sourcetitle": "International Journal of Advertising", @@ -32706,7 +2431,7 @@ } }, { - "key": "85133254567", + "key": 85133254567, "attributes": { "title": "Overturning Roe v Wade has had an immediate chilling effect on reproductive healthcare", "sourcetitle": "The BMJ", @@ -32724,7 +2449,7 @@ } }, { - "key": "85105971699", + "key": 85105971699, "attributes": { "title": "\u201cI don\u2019t think you belong in here:\u201d The impact of gender segregated bathrooms on the safety, health, and equality of transgender people", "sourcetitle": "Journal of Gay and Lesbian Social Services", @@ -32742,7 +2467,7 @@ } }, { - "key": "85127367153", + "key": 85127367153, "attributes": { "title": "Social Emotions and the Legitimation of the Fertility Technology Market", "sourcetitle": "Journal of Consumer Research", @@ -32760,7 +2485,7 @@ } }, { - "key": "85092360259", + "key": 85092360259, "attributes": { "title": "LGBTIQ + identities in tourism and leisure research: a systematic qualitative literature review", "sourcetitle": "Journal of Sustainable Tourism", @@ -32778,7 +2503,7 @@ } }, { - "key": "85118669874", + "key": 85118669874, "attributes": { "title": "Diversity, Equity, and Inclusion (DEI) in the Journal of Consumer Research: A Curation and Research Agenda", "sourcetitle": "Journal of Consumer Research", @@ -32796,7 +2521,7 @@ } }, { - "key": "85128320614", + "key": 85128320614, "attributes": { "title": "Sarcastic or Assertive: How Should Brands Reply to Consumers\u2019 Uncivil Comments on Social Media in the Context of Brand Activism?", "sourcetitle": "Journal of Interactive Marketing", @@ -32814,7 +2539,7 @@ } }, { - "key": "85130073483", + "key": 85130073483, "attributes": { "title": "Stigmas that matter: Diffracting marketing stigma theoretics", "sourcetitle": "Marketing Theory", @@ -32832,7 +2557,7 @@ } }, { - "key": "85133569399", + "key": 85133569399, "attributes": { "title": "\u2018We're all Born Naked and the Rest is Drag\u2019: Spectacularization of Core Stigma in RuPaul's Drag Race", "sourcetitle": "Journal of Management Studies", @@ -32850,7 +2575,7 @@ } }, { - "key": "85121384557", + "key": 85121384557, "attributes": { "title": "\u2018Which part of the day is (wo)man o\u2019clock?\u2019: Desires, urges and possibilities of (un)becoming", "sourcetitle": "Marketing Theory", @@ -32868,7 +2593,7 @@ } }, { - "key": "85125136913", + "key": 85125136913, "attributes": { "title": "LGBT-Inclusive Representation in Entertainment Products and Its Market Response: Evidence from Field and Lab", "sourcetitle": "Journal of Business Ethics", @@ -32886,7 +2611,7 @@ } }, { - "key": "85137228326", + "key": 85137228326, "attributes": { "title": "\u201cGenerally, I live a lie\u201d: Transgender consumer experiences and responses to symbolic violence", "sourcetitle": "Journal of Consumer Affairs", @@ -32904,7 +2629,7 @@ } }, { - "key": "85132629121", + "key": 85132629121, "attributes": { "title": "Almost Equal: Consumption under Fragmented Stigma", "sourcetitle": "Journal of Consumer Research", @@ -32922,7 +2647,7 @@ } }, { - "key": "85130233700", + "key": 85130233700, "attributes": { "title": "Effects of physical appearance of ad endorsers featured in gay-targeted ads, explained by endorser match-up and identification", "sourcetitle": "International Journal of Advertising", @@ -32940,13 +2665,8 @@ } }, { - "key": "85167334948", + "key": 85167334948, "attributes": { - "title": "MindMiner: Uncovering linguistic markers of mind perception as a new lens to understand consumer\u2013smart object relationships", - "sourcetitle": "Journal of Consumer Psychology", - "author": "Hartmann J.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.007619047619047619, "betweenness": 0.0, "closeness": 0.0, @@ -32957,7 +2677,7 @@ } }, { - "key": "85125920040", + "key": 85125920040, "attributes": { "title": "Alexa, what do we know about conversational commerce? Insights from a systematic literature review", "sourcetitle": "Psychology and Marketing", @@ -32975,7 +2695,7 @@ } }, { - "key": "85160618860", + "key": 85160618860, "attributes": { "title": "Voice analytics in the wild: Validity and predictive accuracy of common audio-recording devices", "sourcetitle": "Behavior Research Methods", @@ -32993,13 +2713,8 @@ } }, { - "key": "85166630306", + "key": 85166630306, "attributes": { - "title": "The effect of subjectivity and objectivity in online reviews: A convolutional neural network approach", - "sourcetitle": "Journal of Consumer Psychology", - "author": "Park S.K.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.005714285714285714, "betweenness": 0.0, "closeness": 0.0, @@ -33010,7 +2725,7 @@ } }, { - "key": "85116722502", + "key": 85116722502, "attributes": { "title": "Do sensory reviews make more sense? The mediation of objective perception in online review helpfulness", "sourcetitle": "Journal of Research in Interactive Marketing", @@ -33028,7 +2743,7 @@ } }, { - "key": "85140001824", + "key": 85140001824, "attributes": { "title": "Differential effects of analytical versus emotional rhetorical style on review helpfulness", "sourcetitle": "Journal of Business Research", @@ -33046,7 +2761,7 @@ } }, { - "key": "85166668493", + "key": 85166668493, "attributes": { "title": "Rejections Are More Contagious than Choices: How Another's Decisions Shape Our Own", "sourcetitle": "Journal of Consumer Research", @@ -33064,13 +2779,8 @@ } }, { - "key": "85166624123", + "key": 85166624123, "attributes": { - "title": "Speedy activists: How firm response time to sociopolitical events influences consumer behavior", - "sourcetitle": "Journal of Consumer Psychology", - "author": "Nam J.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.01904761904761905, "betweenness": 0.0, "closeness": 0.0, @@ -33081,7 +2791,7 @@ } }, { - 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"key": "85145937750", + "key": 85145937750, "attributes": { "title": "Instrumental Goal Activation Increases Online Petition Support Across Languages", "sourcetitle": "Journal of Personality and Social Psychology", @@ -33470,7 +3175,7 @@ } }, { - "key": "85126899237", + "key": 85126899237, "attributes": { "title": "Linguistic measures of psychological distance track symptom levels and treatment outcomes in a large set of psychotherapy transcripts", "sourcetitle": "Proceedings of the National Academy of Sciences of the United States of America", @@ -33488,7 +3193,7 @@ } }, { - "key": "85128365682", + "key": 85128365682, "attributes": { "title": "Syntax and the Illusion of Fit: How Grammatical Subject Influences Persuasion", "sourcetitle": "Journal of Consumer Research", @@ -33506,13 +3211,8 @@ } }, { - "key": "85165413235", + "key": 85165413235, "attributes": { - "title": "How construal\u2013regulatory mode fit increases social media sharing", - "sourcetitle": "Journal of Consumer Psychology", - 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How expected and actual nutritional value affect the content and linguistic characteristics of online reviews for food products", - "sourcetitle": "Journal of Consumer Psychology", - "author": "Wang Y.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.03428571428571429, "betweenness": 0.0, "closeness": 0.0, @@ -33612,7 +3307,7 @@ } }, { - "key": "85121749320", + "key": 85121749320, "attributes": { "title": "Hype News Diffusion and Risk of Misinformation: The Oz Effect in Health Care", "sourcetitle": "Journal of Marketing Research", @@ -33630,7 +3325,7 @@ } }, { - "key": "85126841748", + "key": 85126841748, "attributes": { "title": "Identifying attributes of wineries that increase visitor satisfaction and dissatisfaction: Applying an aspect extraction approach to online reviews", "sourcetitle": "Tourism Management", @@ -33648,7 +3343,7 @@ } }, { - "key": "85126136734", + "key": 85126136734, "attributes": { "title": "How much is too much? Estimating tourism carrying capacity in urban context using sentiment analysis", "sourcetitle": "Tourism Management", @@ -33666,7 +3361,7 @@ } }, { - "key": "85126629453", + "key": 85126629453, "attributes": { "title": "Effect of online review sentiment on product sales: The moderating role of review credibility perception", "sourcetitle": "Computers in Human Behavior", @@ -33684,7 +3379,7 @@ } }, { - "key": "85123017411", + "key": 85123017411, "attributes": { "title": "Examining the influence of linguistic characteristics of online managerial response on return customers\u2019 change in satisfaction with hotels", "sourcetitle": "International Journal of Hospitality Management", @@ -33702,7 +3397,7 @@ } }, { - "key": "85127369781", + "key": 85127369781, "attributes": { "title": "Beyond anger: A neutralization perspective of customer revenge", "sourcetitle": "Journal of Business Research", @@ -33720,7 +3415,7 @@ } }, { - "key": "85102511342", + "key": 85102511342, "attributes": { "title": "The informational value of multi-attribute online consumer reviews: A text mining approach", "sourcetitle": "Journal of Retailing and Consumer Services", @@ -33738,7 +3433,7 @@ } }, { - 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An investigation of video influencers\u2019 authenticity management strategies", "sourcetitle": "Journal of the Academy of Marketing Science", @@ -34114,7 +3799,7 @@ } }, { - "key": "85124362439", + "key": 85124362439, "attributes": { "title": "Social media influencers as human brands: an interactive marketing perspective", "sourcetitle": "Journal of Research in Interactive Marketing", @@ -34132,7 +3817,7 @@ } }, { - "key": "85122682108", + "key": 85122682108, "attributes": { "title": "Online influencer marketing", "sourcetitle": "Journal of the Academy of Marketing Science", @@ -34150,7 +3835,7 @@ } }, { - "key": "85135594501", + "key": 85135594501, "attributes": { "title": "DYNAMIC ADVERTISING INSERTION STRATEGY WITH MOMENT-TO-MOMENT DATA USING SENTIMENT ANALYSIS: THE CASE OF DANMAKU VIDEO", "sourcetitle": "Journal of Electronic Commerce Research", @@ -34168,7 +3853,7 @@ } }, { - "key": "85127403749", + "key": 85127403749, "attributes": { "title": "From direct marketing to interactive marketing: a retrospective review of the Journal of Research in Interactive Marketing", "sourcetitle": "Journal of Research in Interactive Marketing", @@ -34186,7 +3871,7 @@ } }, { - "key": "85122149735", + "key": 85122149735, "attributes": { "title": "\u201cYOU POST, I TRAVEL.\u201d Bloggers' credibility, digital engagement, and travelers' behavioral intention: The mediating role of hedonic and utilitarian motivations", "sourcetitle": "Psychology and Marketing", @@ -34204,7 +3889,7 @@ } }, { - "key": "85114668033", + "key": 85114668033, "attributes": { "title": "Sponsored consumer-generated advertising in the digital era: what prompts individuals to generate video ads, and what creative strategies do they adopt?", "sourcetitle": "International Journal of Advertising", @@ -34222,7 +3907,7 @@ } }, { - "key": "85163158200", + "key": 85163158200, "attributes": { "centrality": 0.0038095238095238095, "betweenness": 0.0, @@ -34234,7 +3919,7 @@ } }, { - "key": "85134395206", + "key": 85134395206, "attributes": { "title": "Styleformer: Transformer based Generative Adversarial Networks with Style Vector", "sourcetitle": "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition", @@ -34252,7 +3937,7 @@ } }, { - "key": "85141229542", + "key": 85141229542, "attributes": { "title": "Style Transformer for Image Inversion and Editing", "sourcetitle": "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition", @@ -34270,13 +3955,8 @@ } }, { - "key": "85162774955", + "key": 85162774955, "attributes": { - "title": "Words Meet Photos: When and Why Photos Increase Review Helpfulness", - "sourcetitle": "Journal of Marketing Research", - "author": "Ceylan G.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.005714285714285714, "betweenness": 0.0, "closeness": 0.0, @@ -34287,7 +3967,7 @@ } }, { - "key": "85106970413", + "key": 85106970413, "attributes": { "title": "Looks Clear and Sounds Familiar: How Consumers Form Inferential Beliefs About Luxury Hotel Service Quality", "sourcetitle": "Cornell Hospitality Quarterly", @@ -34305,7 +3985,7 @@ } }, { - "key": "85126827345", + "key": 85126827345, "attributes": { "title": "Relevance - Reloaded and Recoded", "sourcetitle": "Journal of Consumer Research", @@ -34323,7 +4003,7 @@ } }, { - "key": "85138462024", + "key": 85138462024, "attributes": { "title": "What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features", "sourcetitle": "Management Science", @@ -34341,13 +4021,8 @@ } }, { - "key": "85161509158", + "key": 85161509158, "attributes": { - "title": "What affects the use of green technology in hotels? Assessing hotel management viewpoint using natural language processing based qualitative study", - "sourcetitle": "Journal of Hospitality Marketing and Management", - "author": "Ray A.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.017142857142857144, "betweenness": 0.0, "closeness": 0.0, @@ -34358,7 +4033,7 @@ } }, { - "key": "85133676143", + "key": 85133676143, "attributes": { "title": "How can topic-modelling of user-reviews reshape market surveys? Exploring factors influencing usage intention of e-learning services through a novel multi-method approach", "sourcetitle": "International Journal of Business Information Systems", @@ -34376,7 +4051,7 @@ } }, { - "key": "85143658427", + "key": 85143658427, "attributes": { "title": "Antecedents of labor shortage in the rural hospitality industry: a comparative study of employees and employers", "sourcetitle": "Journal of Hospitality and Tourism Insights", @@ -34394,7 +4069,7 @@ } }, { - "key": "85123451919", + "key": 85123451919, "attributes": { "title": "Impact of green human resource management practices on the environmental performance of green hotels", "sourcetitle": "Journal of Hospitality Marketing and Management", @@ -34412,7 +4087,7 @@ } }, { - "key": "85149184200", + "key": 85149184200, "attributes": { "title": "Paradigm of Green Technologies in Hospitality Industry and its Sustainability Analytics", "sourcetitle": "2022 International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2022", @@ -34430,7 +4105,7 @@ } }, { - "key": "85123905885", + "key": 85123905885, "attributes": { "title": "Digital Economy and Health: Does Green Technology Matter in BRICS Economies?", "sourcetitle": "Frontiers in Public Health", @@ -34448,7 +4123,7 @@ } }, { - "key": "85143399304", + "key": 85143399304, "attributes": { "title": "A review of green practices and initiatives from stakeholder\u2019s perspectives towards sustainable hotel operations and performance impact", "sourcetitle": "Journal of Facilities Management", @@ -34466,7 +4141,7 @@ } }, { - "key": "85107458763", + "key": 85107458763, "attributes": { "title": "Proactive environmental strategies in the hotel industry: eco-innovation, green competitive advantage, and green core competence", "sourcetitle": "Journal of Sustainable Tourism", @@ -34484,7 +4159,7 @@ } }, { - "key": "85137100845", + "key": 85137100845, "attributes": { "title": "Environmental Skills Gaps in Tourism and Hospitality Organisations: Evidence from Europe", "sourcetitle": "Tourism", @@ -34502,13 +4177,8 @@ } }, { - "key": "85160700281", + "key": 85160700281, "attributes": { - "title": "The role of affective ties in the asymmetrical relationship between student satisfaction and loyalty. Comparative study of European business schools", - "sourcetitle": "Journal of Marketing for Higher Education", - "author": "Tandilashvili N.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.0038095238095238095, "betweenness": 0.0, "closeness": 0.0, @@ -34519,7 +4189,7 @@ } }, { - "key": "85097098038", + "key": 85097098038, "attributes": { "title": "The influence of course experience, satisfaction, and loyalty on students\u2019 word-of-mouth and re-enrolment intentions", "sourcetitle": "Journal of Marketing for Higher Education", @@ -34537,7 +4207,7 @@ } }, { - "key": "85111125597", + "key": 85111125597, "attributes": { "title": "Student-to-Student Interactions in Marketing Education: A Critical Incident Technique-Based Inquiry Into Drivers of Students\u2019 (Dis)Satisfaction", "sourcetitle": "Journal of Marketing Education", @@ -34555,13 +4225,8 @@ } }, { - "key": "85160170305", + "key": 85160170305, "attributes": { - "title": "Deep Learning Applications for Interactive Marketing in the Contemporary Digital Age", - 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Interview with Open AI\u2019s ChatGPT", "sourcetitle": "European Journal of Tourism Research", @@ -35091,7 +4741,7 @@ } }, { - "key": "85150364293", + "key": 85150364293, "attributes": { "title": "ChatGPT for good? On opportunities and challenges of large language models for education", "sourcetitle": "Learning and Individual Differences", @@ -35109,7 +4759,7 @@ } }, { - "key": "85118622208", + "key": 85118622208, "attributes": { "title": "Analysis of the attributes of smart tourism technologies in destination chatbots that influence tourist satisfaction", "sourcetitle": "Current Issues in Tourism", @@ -35127,7 +4777,7 @@ } }, { - "key": "85150995073", + "key": 85150995073, "attributes": { "title": "ChatGPT and consumers: Benefits, Pitfalls and Future Research Agenda", "sourcetitle": "International Journal of Consumer Studies", @@ -35145,7 +4795,7 @@ } }, { - "key": "85141023258", + "key": 85141023258, "attributes": { "title": "New Insights into Consumers\u2019 Intention to Continue Using Chatbots in the Tourism Context", "sourcetitle": "Journal of Quality Assurance in Hospitality and Tourism", @@ -35163,7 +4813,7 @@ } }, { - "key": "85141958028", + "key": 85141958028, "attributes": { "title": "Airline CEO\u2019s AI system for driving personalization", "sourcetitle": "Journal of Revenue and Pricing Management", @@ -35181,7 +4831,7 @@ } }, { - "key": "85151154236", + "key": 85151154236, "attributes": { "title": "ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns", "sourcetitle": "Healthcare (Switzerland)", @@ -35199,7 +4849,7 @@ } }, { - "key": "85148704172", + "key": 85148704172, "attributes": { "title": "What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education", "sourcetitle": "Smart Learning Environments", @@ -35217,7 +4867,7 @@ } }, { - "key": "85147384559", + "key": 85147384559, "attributes": { "title": "ChatGPT: five priorities for research", "sourcetitle": "Nature", @@ -35235,7 +4885,7 @@ } }, { - "key": "85149470349", + "key": 85149470349, "attributes": { "title": "What Does ChatGPT Say: The DAO from Algorithmic Intelligence to Linguistic Intelligence", "sourcetitle": "IEEE/CAA Journal of Automatica Sinica", @@ -35253,13 +4903,8 @@ } }, { - "key": "85158916650", + "key": 85158916650, "attributes": { - "title": "Research on online shopping contextual cues: refining classification from text mining", - "sourcetitle": "Asia Pacific Journal of Marketing and Logistics", - "author": "Wang L.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.015238095238095238, "betweenness": 0.0, "closeness": 0.0, @@ -35270,7 +4915,7 @@ } }, { - "key": "85123205415", + "key": 85123205415, "attributes": { "title": "Exploring the challenges of remote work on Twitter users' sentiments: From digital technology development to a post-pandemic era", "sourcetitle": "Journal of Business Research", @@ -35288,7 +4933,7 @@ } }, { - "key": "85136465236", + "key": 85136465236, "attributes": { "title": "Context-aware incremental clustering of alerts in monitoring systems", "sourcetitle": "Expert Systems with Applications", @@ -35306,7 +4951,7 @@ } }, { - "key": "85129507705", + "key": 85129507705, "attributes": { "title": "Big arena, small potatoes: A mixed-methods investigation of atmospheric cues in live-streaming e-commerce", "sourcetitle": "Decision Support Systems", @@ -35324,7 +4969,7 @@ } }, { - "key": "85131263113", + "key": 85131263113, "attributes": { "title": "Spatio-temporal and contextual cues to support reflection in physical activity tracking", "sourcetitle": "International Journal of Human Computer Studies", @@ -35342,7 +4987,7 @@ } }, { - "key": "85129544850", + "key": 85129544850, "attributes": { "title": "Is this food healthy? The impact of lay beliefs and contextual cues on food healthiness perception and consumption", "sourcetitle": "Current Opinion in Psychology", @@ -35360,7 +5005,7 @@ } }, { - "key": "85135893293", + "key": 85135893293, "attributes": { "title": "A semantic matching approach addressing multidimensional representations for web service discovery", "sourcetitle": "Expert Systems with Applications", @@ -35378,7 +5023,7 @@ } }, { - "key": "85121364549", + "key": 85121364549, "attributes": { "title": "Changes in the effect of credence cues on restaurant delivery service under different health risks", "sourcetitle": "International Journal of Contemporary Hospitality Management", @@ -35396,7 +5041,7 @@ } }, { - "key": "85139859753", + "key": 85139859753, "attributes": { "title": "Factors affecting text mining based stock prediction: Text feature representations, machine learning models, and news platforms", "sourcetitle": "Applied Soft Computing", @@ -35414,13 +5059,8 @@ } }, { - "key": "85158148454", + "key": 85158148454, "attributes": { - "title": "What Holds Attention? Linguistic Drivers of Engagement", - "sourcetitle": "Journal of Marketing", - "author": "Berger J.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.005714285714285714, "betweenness": 0.0, "closeness": 0.0, @@ -35431,7 +5071,7 @@ } }, { - "key": "85135857050", + "key": 85135857050, "attributes": { "title": "I share, therefore I know? Sharing online content - even without reading it - inflates subjective knowledge", "sourcetitle": "Journal of Consumer Psychology", @@ -35449,7 +5089,7 @@ } }, { - "key": "85126628630", + "key": 85126628630, "attributes": { "title": "How Does the Adoption of Ad Blockers Affect News Consumption?", "sourcetitle": "Journal of Marketing Research", @@ -35467,7 +5107,7 @@ } }, { - "key": "85136339950", + "key": 85136339950, "attributes": { "title": "The Speed of Stories: Semantic Progression and Narrative Success", "sourcetitle": "Journal of Experimental Psychology: General", @@ -35485,13 +5125,8 @@ } }, { - "key": "85153032773", + "key": 85153032773, "attributes": { - "title": "Understanding Customer Participation Dynamics: The Case of the Subscription Box", - "sourcetitle": "Journal of Marketing", - "author": "Umashankar N.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.0038095238095238095, "betweenness": 0.0, "closeness": 0.0, @@ -35502,7 +5137,7 @@ } }, { - "key": "85130376503", + "key": 85130376503, "attributes": { "title": "Will he buy a surprise? Gender differences in the purchase of surprise offerings", "sourcetitle": "Journal of Retailing", @@ -35520,7 +5155,7 @@ } }, { - "key": "85124909851", + "key": 85124909851, "attributes": { "title": "How consumer digital signals are reshaping the customer journey", "sourcetitle": "Journal of the Academy of Marketing Science", @@ -35538,13 +5173,8 @@ } }, { - "key": "85152800674", + "key": 85152800674, "attributes": { - "title": "\u201cInside\u201d versus \u201coutside\u201d trends in consumer research", - "sourcetitle": "Journal of Consumer Psychology", - "author": "Camilleri E.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.017142857142857144, "betweenness": 0.0, "closeness": 0.0, @@ -35555,7 +5185,7 @@ } }, { - "key": "85112165538", + "key": 85112165538, "attributes": { "title": "Social Marginalization Motivates Indiscriminate Sharing of COVID-19 News on Social Media", "sourcetitle": "Journal of the Association for Consumer Research", @@ -35573,7 +5203,7 @@ } }, { - "key": "85114191346", + "key": 85114191346, "attributes": { "title": "(Not) Near and Dear: COVID-19 Concerns Increase Consumer Preference for Products That Are Not \u201cNear Me\u201d", "sourcetitle": "Journal of the Association for Consumer Research", @@ -35591,7 +5221,7 @@ } }, { - "key": "85130985738", + "key": 85130985738, "attributes": { "title": "Bringing Our Values to the Table: Political Ideology, Food Waste, and Overconsumption", "sourcetitle": "Journal of the Association for Consumer Research", @@ -35609,7 +5239,7 @@ } }, { - "key": "85127814047", + "key": 85127814047, "attributes": { "title": "Engaging Consumers with Environmental Sustainability Initiatives: Consumer Global\u2013Local Identity and Global Brand Messaging", "sourcetitle": "Journal of Marketing Research", @@ -35627,7 +5257,7 @@ } }, { - "key": "85125097777", + "key": 85125097777, "attributes": { "title": "The impact of the COVID-19 pandemic on grocery shopper behaviour: Analysis of shopper behaviour change using store transaction data", "sourcetitle": "Journal of Consumer Behaviour", @@ -35645,7 +5275,7 @@ } }, { - "key": "85128452984", + "key": 85128452984, "attributes": { "title": "Bayesian Consumer Profiling: How to Estimate Consumer Characteristics from Aggregate Data", "sourcetitle": "Journal of Marketing Research", @@ -35663,7 +5293,7 @@ } }, { - "key": "85141454821", + "key": 85141454821, "attributes": { "title": "Plant power: SEEDing our future with plant-based eating", "sourcetitle": "Journal of Consumer Psychology", @@ -35681,7 +5311,7 @@ } }, { - "key": "85146358514", + "key": 85146358514, "attributes": { "title": "Robots or humans for disaster response? Impact on consumer prosociality and possible explanations", "sourcetitle": "Journal of Consumer Psychology", @@ -35699,7 +5329,7 @@ } }, { - "key": "85101928307", + "key": 85101928307, "attributes": { "title": "Pricing Fairness in a Pandemic: Navigating Unintended Changes to Value or Cost", "sourcetitle": "Journal of the Association for Consumer Research", @@ -35717,13 +5347,8 @@ } }, { - "key": "85151960432", + "key": 85151960432, "attributes": { - "title": "Extracting marketing information from product reviews: a comparative study of latent semantic analysis and probabilistic latent semantic analysis", - "sourcetitle": "Journal of Marketing Analytics", - "author": "Ahmad S.N.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.007619047619047619, "betweenness": 0.0, "closeness": 0.0, @@ -35734,7 +5359,7 @@ } }, { - "key": "85131077854", + "key": 85131077854, "attributes": { "title": "The combinatory role of online ratings and reviews in mobile app downloads: an empirical investigation of gaming and productivity apps from their initial app store launch", "sourcetitle": "Journal of Marketing Analytics", @@ -35752,7 +5377,7 @@ } }, { - 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"title": "Cross-national consumer research using structural topic modelling: Consumers' approach-avoidance behaviours", - "sourcetitle": "International Journal of Consumer Studies", - "author": "Jung M.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.009523809523809525, "betweenness": 0.0, "closeness": 0.0, @@ -35965,7 +5575,7 @@ } }, { - "key": "85119197890", + "key": 85119197890, "attributes": { "title": "Using structural topic modeling to gain insight into challenges faced by leaders", "sourcetitle": "Leadership Quarterly", @@ -35983,7 +5593,7 @@ } }, { - "key": "85101851141", + "key": 85101851141, "attributes": { "title": "Do parasocial interactions and vicarious experiences in the beauty YouTube channels promote consumer purchase intention?", "sourcetitle": "International Journal of Consumer Studies", @@ -36001,7 +5611,7 @@ } }, { - "key": "85135826495", + "key": 85135826495, "attributes": { "title": "Drivers of behavioral intention among non-Muslims toward halal cosmetics: evidence from Indonesia, Malaysia, and Singapore", "sourcetitle": "Journal of Islamic Accounting and Business Research", @@ -36019,7 +5629,7 @@ } }, { - 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News Media Coverage of COVID-19 in China Daily", "sourcetitle": "Journalism Practice", @@ -36037,7 +5647,7 @@ } }, { - "key": "85119355264", + "key": 85119355264, "attributes": { "title": "Assessing Malaysia and Indonesia as emerging retail markets: an institution-based view", "sourcetitle": "International Journal of Retail and Distribution Management", @@ -36055,13 +5665,8 @@ } }, { - "key": "85150739173", + "key": 85150739173, "attributes": { - "title": "Style, content, and the success of ideas", - "sourcetitle": "Journal of Consumer Psychology", - "author": "Boghrati R.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.0019047619047619048, "betweenness": 0.0, "closeness": 0.0, @@ -36072,13 +5677,8 @@ } }, { - "key": "85150490983", + "key": 85150490983, "attributes": { - "title": "Perception and gaze of diaspora: Analysis of affective, cognitive, & cultural factors in tourism", - "sourcetitle": "Journal of Vacation Marketing", - "author": "Wang Q.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.013333333333333332, "betweenness": 0.0, "closeness": 0.0, @@ -36089,7 +5689,7 @@ } }, { - "key": "85136913317", + "key": 85136913317, "attributes": { "title": "Cognitive image, affective image, cultural dimensions, and conative image: A new conceptual framework", "sourcetitle": "Frontiers in Psychology", @@ -36107,7 +5707,7 @@ } }, { - "key": "85130600835", + "key": 85130600835, "attributes": { "title": "EXPLORING COMMUNITY FESTIVALS IN THE CONTEXT OF THE CHINESE DIASPORA", "sourcetitle": "Event Management", @@ -36125,7 +5725,7 @@ } }, { - "key": "85117857429", + "key": 85117857429, "attributes": { "title": "Tourist gazes through photographs", "sourcetitle": "Journal of Vacation Marketing", @@ -36143,7 +5743,7 @@ } }, { - "key": "85147218019", + "key": 85147218019, "attributes": { "title": "Text Mining for Information Professionals: An Uncharted Territory", "sourcetitle": "Text Mining for Information Professionals: An Uncharted Territory", @@ -36161,7 +5761,7 @@ } }, { - "key": "85113742006", + "key": 85113742006, "attributes": { "title": "Chineseness and behavioural complexity: rethinking Chinese tourist gaze studies", "sourcetitle": "Tourism Review", @@ -36179,7 +5779,7 @@ } }, { - "key": "85137658564", + "key": 85137658564, "attributes": { "title": "Tourist gaze upon a slum tourism destination: A case study of Dharavi, India", "sourcetitle": "Journal of Hospitality and Tourism Management", @@ -36197,7 +5797,7 @@ } }, { - "key": "85138789342", + "key": 85138789342, "attributes": { "title": "Structural Relationship between Cognitive Image, Destination Personality and Tourists Motivation", "sourcetitle": "International Journal of Hospitality and Tourism Systems", @@ -36215,13 +5815,8 @@ } }, { - "key": "85149420983", + "key": 85149420983, "attributes": { - "title": "Using Sentiment Analysis to Understand Public Policy Nicknames: Obamacare and the Affordable Care Act", - "sourcetitle": "Journal of Nonprofit and Public Sector Marketing", - "author": "Lappeman J.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.0019047619047619048, "betweenness": 0.0, "closeness": 0.0, @@ -36232,7 +5827,7 @@ } }, { - "key": "85130993641", + "key": 85130993641, "attributes": { "title": "What social media sentiment tells us about why customers churn", "sourcetitle": "Journal of Consumer Marketing", @@ -36250,7 +5845,7 @@ } }, { - "key": "85149113734", + "key": 85149113734, "attributes": { "centrality": 0.0038095238095238095, "betweenness": 0.0, @@ -36262,7 +5857,7 @@ } }, { - "key": "85138489610", + "key": 85138489610, "attributes": { "title": "A Novel Approach on Machine Learning based Data Warehousing for Intelligent Healthcare Services", "sourcetitle": "2022 IEEE Region 10 Symposium, TENSYMP 2022", @@ -36280,7 +5875,7 @@ } }, { - "key": "85139852966", + "key": 85139852966, "attributes": { "title": "Mandibular Canal Segmentation From CBCT Image Using 3D Convolutional Neural Network With scSE Attention", "sourcetitle": "IEEE Access", @@ -36298,7 +5893,7 @@ } }, { - "key": "85147100431", + "key": 85147100431, "attributes": { "centrality": 0.0019047619047619048, "betweenness": 0.0, @@ -36310,7 +5905,7 @@ } }, { - "key": "85134060835", + "key": 85134060835, "attributes": { "title": "Digital exchange compromises: Teetering priorities of consumers and organizations at the iron triangle", "sourcetitle": "Journal of Consumer Affairs", @@ -36328,13 +5923,8 @@ } }, { - "key": "85143898085", + "key": 85143898085, "attributes": { - "title": "Is this advertising or not, and do I care? Perceptions of and opinions regarding hybrid forms of content", - "sourcetitle": "Journal of Marketing Communications", - "author": "St\u00fcrmer L.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.0038095238095238095, "betweenness": 0.0, "closeness": 0.0, @@ -36345,7 +5935,7 @@ } }, { - "key": "85135574979", + "key": 85135574979, "attributes": { "title": "Corporate allies or adversaries: An exploration of the relationship between public relations and marketing among Ghanaian practitioners", "sourcetitle": "Journal of Marketing Communications", @@ -36363,7 +5953,7 @@ } }, { - "key": "85109089966", + "key": 85109089966, "attributes": { "title": "How much journalism is in brand journalism? How brand journalists perceive their roles and blur the boundaries between journalism and strategic communication", "sourcetitle": "Journalism", @@ -36381,13 +5971,8 @@ } }, { - "key": "85141229738", + "key": 85141229738, "attributes": { - "title": "Exploring the factors influencing consumer engagement behavior regarding short-form video advertising: A big data perspective", - "sourcetitle": "Journal of Retailing and Consumer Services", - "author": "Xiao L.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.015238095238095238, "betweenness": 0.0, "closeness": 0.0, @@ -36398,7 +5983,7 @@ } }, { - "key": "85136236273", + "key": 85136236273, "attributes": { "title": "Effects of short-video use on undergraduates\u2019 weight- loss intention: a regulatory mediation model", "sourcetitle": "Current Psychology", @@ -36416,7 +6001,7 @@ } }, { - "key": "85131893460", + "key": 85131893460, "attributes": { "title": "The short video usage motivation and behavior of middle-aged and old users", "sourcetitle": "Library Hi Tech", @@ -36434,7 +6019,7 @@ } }, { - "key": "85135695313", + "key": 85135695313, "attributes": { "title": "The effect of advertising strategies on a short video platform: evidence from TikTok", "sourcetitle": "Industrial Management and Data Systems", @@ -36452,7 +6037,7 @@ } }, { - "key": "85129137939", + "key": 85129137939, "attributes": { "title": "Driving Factors and Moderating Effects Behind Citizen Engagement With Mobile Short-Form Videos", "sourcetitle": "IEEE Access", @@ -36470,7 +6055,7 @@ } }, { - "key": "85125042600", + "key": 85125042600, "attributes": { "title": "How short-form video features influence addiction behavior? Empirical research from the opponent process theory perspective", "sourcetitle": "Information Technology and People", @@ -36488,7 +6073,7 @@ } }, { - "key": "85126119033", + "key": 85126119033, "attributes": { "title": "Cooperative advertising with two local advertising options in a retailer duopoly", "sourcetitle": "Scientia Iranica", @@ -36506,7 +6091,7 @@ } }, { - "key": "85141302744", + "key": 85141302744, "attributes": { "title": "Applying the uses and gratifications theory to identify motivational factors behind young adult's participation in viral social media challenges on TikTok", "sourcetitle": "Human Factors in Healthcare", @@ -36524,7 +6109,7 @@ } }, { - "key": "85118282008", + "key": 85118282008, "attributes": { "title": "Crossed effects of audio-visual environment on indoor soundscape perception for pleasant open-plan office environments", "sourcetitle": "Building and Environment", @@ -36542,13 +6127,8 @@ } }, { - "key": "85139737257", + "key": 85139737257, "attributes": { - "title": "Designing marketing content for social commerce to drive consumer purchase behaviors: A perspective from speech act theory", - "sourcetitle": "Journal of Retailing and Consumer Services", - "author": "Wang F.", - "year": 2023, - "citations_per_year": 0.0, "centrality": 0.02095238095238095, "betweenness": 0.0, "closeness": 0.0, @@ -36559,7 +6139,7 @@ } }, { - "key": "85129949450", + "key": 85129949450, "attributes": { "title": "How customer engagement in the live-streaming affects purchase intention and customer acquisition, E-tailer's perspective", "sourcetitle": "Journal of Retailing and Consumer Services", @@ -36577,7 +6157,7 @@ } }, { - "key": "85135011138", + "key": 85135011138, "attributes": { "title": "Influencer Marketing Effectiveness", "sourcetitle": "Journal of Marketing", @@ -36595,7 +6175,7 @@ } }, { - "key": "85134891004", + "key": 85134891004, "attributes": { "title": "Investigating consumers\u2019 cognitive, emotional, and behavioral engagement in social media brand pages: A natural language processing approach", "sourcetitle": "Electronic Commerce Research and Applications", @@ -36613,7 +6193,7 @@ } }, { - "key": "85134681923", + "key": 85134681923, "attributes": { "title": "Creative Appeals in Firm-Generated Content and Product Performance", "sourcetitle": "Information Systems Research", @@ -36631,7 +6211,7 @@ } }, { - "key": "85129137118", + "key": 85129137118, "attributes": { "title": "Emotional and the normative aspects of customers\u2019 reviews", "sourcetitle": "Journal of Retailing and Consumer Services", @@ -36649,7 +6229,7 @@ } }, { - "key": "85133173389", + "key": 85133173389, "attributes": { "title": "Restaurants\u2019 outdoor signs say more than you think: An enquiry from a linguistic landscape perspective", "sourcetitle": "Journal of Retailing and Consumer Services", @@ -36667,7 +6247,7 @@ } }, { - "key": "85133603498", + "key": 85133603498, "attributes": { "title": "Social media celebrities and new world order. 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A perspective from online reviews", "sourcetitle": "Journal of Hospitality and Tourism Management", @@ -36918,7 +6493,7 @@ } }, { - "key": "85124290309", + "key": 85124290309, "attributes": { "title": "The use of big data analytics to discover customers\u2019 perceptions of and satisfaction with green hotel service quality", "sourcetitle": "Current Issues in Tourism", @@ -36936,7 +6511,7 @@ } }, { - "key": "85103160014", + "key": 85103160014, "attributes": { "title": "Dissatisfaction toward O2O websites: expectation disconfirmation and justice perspective", "sourcetitle": "Asia Pacific Journal of Marketing and Logistics", @@ -36954,7 +6529,7 @@ } }, { - "key": "85124402854", + "key": 85124402854, "attributes": { "title": "Assessing destination satisfaction by social media: An innovative approach using Importance-Performance Analysis", "sourcetitle": "Annals of Tourism Research", @@ -36972,7 +6547,7 @@ } }, { - "key": "85124529183", + "key": 85124529183, "attributes": { "title": "Modeling customer satisfaction through online reviews: A FlowSort group decision model under probabilistic linguistic settings", "sourcetitle": "Expert Systems with Applications", @@ -36990,7 +6565,7 @@ } }, { - "key": "85124240888", + "key": 85124240888, "attributes": { "title": "The moderating effects of entertainers on public engagement through government activities in social media during the COVID-19", "sourcetitle": "Telematics and Informatics", @@ -37008,7 +6583,7 @@ } }, { - "key": "85107269651", + "key": 85107269651, "attributes": { "title": "The Role of Cultural Congruence in the Art Infusion Effect", "sourcetitle": "Journal of Consumer Psychology", @@ -37026,13 +6601,8 @@ } }, { - "key": "85138798648", + "key": 85138798648, "attributes": { - "title": "Internet of Things (IoT) in smart tourism: a literature review", - "sourcetitle": "Spanish Journal of Marketing - ESIC", - "author": "Novera C.N.", - "year": 2022, - "citations_per_year": 2.0, "centrality": 0.0019047619047619048, "betweenness": 0.0, "closeness": 0.0, @@ -37043,7 +6613,7 @@ } }, { - "key": "85122861720", + "key": 85122861720, "attributes": { "title": "Clustering Application for Condition-Based Maintenance in Time-Varying Processes: A Review Using Latent Dirichlet Allocation", "sourcetitle": "Applied Sciences (Switzerland)", @@ -37061,13 +6631,8 @@ } }, { - "key": "85153078307", + "key": 85153078307, "attributes": { - "title": "Offline Context Affects Online Reviews: The Effect of Post-Consumption Weather", - "sourcetitle": "Journal of Consumer Research", - "author": "Brandes L.", - "year": 2022, - "citations_per_year": 1.0, "centrality": 0.0019047619047619048, "betweenness": 0.0, "closeness": 0.0, @@ -37078,7 +6643,7 @@ } }, { - "key": "85130480512", + "key": 85130480512, "attributes": { "title": "Extremity Bias in Online Reviews: The Role of Attrition", "sourcetitle": "Journal of Marketing Research", @@ -37096,13 +6661,8 @@ } }, { - "key": "85140003141", + "key": 85140003141, "attributes": { - "title": "Does celebrity attachment influence brand attachment and brand loyalty in celebrity endorsement? 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Exploration of consumers\u2019 motives for following influencers and the role of materialism", "sourcetitle": "International Journal of Advertising", @@ -37292,7 +6847,7 @@ } }, { - "key": "85125047209", + "key": 85125047209, "attributes": { "title": "From Ignorance to Distrust: The Public \u201cDiscovery\u201d of COVID-19 Around International Women\u2019s Day in Spain", "sourcetitle": "International Journal of Communication", @@ -37310,7 +6865,7 @@ } }, { - "key": "85134150091", + "key": 85134150091, "attributes": { "title": "Consumers' identity signaling towards social groups: The effects of dissociative desire on brand prominence preferences", "sourcetitle": "Psychology and Marketing", @@ -37328,13 +6883,8 @@ } }, { - "key": "85120610290", + "key": 85120610290, "attributes": { - "title": "Cooperator or supporter: how can cross-boundary Macau\u2013Zhuhai metropolis promote regional tourism together?", - "sourcetitle": "Asia Pacific Journal of Marketing and Logistics", - "author": "Song X.", - "year": 2022, - "citations_per_year": 5.0, "centrality": 0.0019047619047619048, "betweenness": 0.0, "closeness": 0.0, @@ -37345,7 +6895,7 @@ } }, { - "key": "85106326049", + "key": 85106326049, "attributes": { "title": "The role of a mega-sporting event in attracting domestic tourists: the case of Seoul", "sourcetitle": "Asia Pacific Journal of Marketing and Logistics", @@ -37363,13 +6913,8 @@ } }, { - "key": "85139848262", + "key": 85139848262, "attributes": { - "title": "Text-mining 10-K (annual) reports: A guide for B2B marketing research", - "sourcetitle": "Industrial Marketing Management", - "author": "Cooper H.B.", - "year": 2022, - "citations_per_year": 2.0, "centrality": 0.009523809523809525, "betweenness": 0.0, "closeness": 0.0, @@ -37380,7 +6925,7 @@ } }, { - "key": "85136468469", + "key": 85136468469, "attributes": { "title": "From mining to meaning: How B2B marketers can leverage text to inform strategy", "sourcetitle": "Industrial Marketing Management", @@ -37398,7 +6943,7 @@ } }, { - "key": "85139877569", + "key": 85139877569, "attributes": { "title": "Handbook of business-to-business marketing", "sourcetitle": "Handbook of Business-to-Business Marketing", @@ -37416,7 +6961,7 @@ } }, { - "key": "85131535046", + "key": 85131535046, "attributes": { "title": "Artificial intelligence focus and firm performance", "sourcetitle": "Journal of the Academy of Marketing Science", @@ -37434,7 +6979,7 @@ } }, { - "key": "85124238325", + "key": 85124238325, "attributes": { "title": "Clearing the paradigmatic fog \u2014 how to move forward in business marketing research", "sourcetitle": "Industrial Marketing Management", @@ -37452,7 +6997,7 @@ } }, { - "key": "85139858876", + "key": 85139858876, "attributes": { "title": "Business-to-business marketing: Looking back, looking forward", "sourcetitle": "Handbook of Business-to-Business Marketing", @@ -37470,7 +7015,7 @@ } }, { - "key": "85124768148", + "key": 85124768148, "attributes": { "title": "The antecedent and consequences of brand competence: Focusing on the moderating role of the type of server in the restaurant industry", "sourcetitle": "Journal of Hospitality and Tourism Management", @@ -37488,7 +7033,7 @@ } }, { - "key": "85111169159", + "key": 85111169159, "attributes": { "title": "Food lifestyle patterns among contemporary food shoppers", "sourcetitle": "International Journal of Consumer Studies", @@ -37506,7 +7051,7 @@ } }, { - "key": "85109761157", + "key": 85109761157, "attributes": { "title": "Does online chatter matter for consumer behaviour? A priming experiment on organic food", "sourcetitle": "International Journal of Consumer Studies", @@ -37524,13 +7069,8 @@ } }, { - "key": "85137626292", + "key": 85137626292, "attributes": { - "title": "Empathy and EGO-drive in the B2B salesforce: Impacts on job satisfaction", - "sourcetitle": "Industrial Marketing Management", - "author": "Treen E.", - "year": 2022, - "citations_per_year": 0.0, "centrality": 0.0019047619047619048, "betweenness": 0.0, "closeness": 0.0, @@ -37541,7 +7081,7 @@ } }, { - "key": "85121034410", + "key": 85121034410, "attributes": { "title": "The impact of self-service versus interpersonal contact on customer\u2013brand relationship in the time of frontline technology infusion", "sourcetitle": "Psychology and Marketing", @@ -37559,7 +7099,7 @@ } }, { - "key": "85134523493", + "key": 85134523493, "attributes": { "title": "The market value of rhetorical signals in technology licensing contracts", "sourcetitle": "Industrial Marketing Management", @@ -37577,7 +7117,7 @@ } }, { - "key": "85130049895", + "key": 85130049895, "attributes": { "title": "That\u2019s So Instagrammable! Understanding How Environments Generate Indirect Advertising by Cueing Consumer-Generated Content", "sourcetitle": "Journal of Advertising", @@ -37595,7 +7135,7 @@ } }, { - "key": "85134811050", + "key": 85134811050, "attributes": { "title": "Looking through the Glassdoor: The stories that B2B salespeople tell", "sourcetitle": "Industrial Marketing Management", @@ -37613,13 +7153,8 @@ } }, { - "key": "85127426396", + "key": 85127426396, "attributes": { - "title": "Understanding digital consumer: A review, synthesis, and future research agenda", - "sourcetitle": "International Journal of Consumer Studies", - "author": "Sa\u011fkaya G\u00fcng\u00f6r A.", - "year": 2022, - "citations_per_year": 9.0, "centrality": 0.005714285714285714, "betweenness": 0.0, "closeness": 0.0, @@ -37630,7 +7165,7 @@ } }, { - "key": "85131271575", + "key": 85131271575, "attributes": { "title": "Just walk out: the effect of AI-enabled checkouts", "sourcetitle": "European Journal of Marketing", @@ -37648,13 +7183,8 @@ } }, { - "key": "85107723237", + "key": 85107723237, "attributes": { - "title": "Maq\u0101\u1e63id al-Shar\u012b\u2018ah on Islamic banking performance in Indonesia: a knowledge discovery via text mining", - "sourcetitle": "Journal of Islamic Marketing", - "author": "Hudaefi F.A.", - "year": 2022, - "citations_per_year": 12.0, "centrality": 0.005714285714285714, "betweenness": 0.0, "closeness": 0.0, @@ -37665,7 +7195,7 @@ } }, { - "key": "85066996919", + "key": 85066996919, "attributes": { "title": "Online disclosure practices of halal-friendly hotels", "sourcetitle": "Journal of Islamic Marketing", @@ -37683,7 +7213,7 @@ } }, { - "key": "85096781617", + "key": 85096781617, "attributes": { "title": "Analysing Islamic banking ethical performance from Maq\u0101\u1e63id al-Shar\u012b\u2018ah perspective: evidence from Indonesia", "sourcetitle": "Journal of Sustainable Finance and Investment", @@ -37701,7 +7231,7 @@ } }, { - "key": "85095615822", + "key": 85095615822, "attributes": { "title": "Exploring the motives behind the purchase of western imported food products. A phenomenological study from a Muslim-dominated region", "sourcetitle": "Journal of Islamic Marketing", @@ -37719,13 +7249,8 @@ } }, { - "key": "85133618737", + "key": 85133618737, "attributes": { - "title": "Emerging Research Trends in Marketing: A Review of Australasian Marketing Journal", - "sourcetitle": "Australasian Marketing Journal", - "author": "Thaichon P.", - "year": 2022, - "citations_per_year": 2.0, "centrality": 0.03619047619047619, "betweenness": 0.0, "closeness": 0.0, @@ -37736,7 +7261,7 @@ } }, { - "key": "85126816719", + "key": 85126816719, "attributes": { "title": "Marketing Scholarship and the Sustainable Development Goals: Thoughts on Moving Forward", "sourcetitle": "Australasian Marketing Journal", @@ -37754,7 +7279,7 @@ } }, { - "key": "85126812957", + "key": 85126812957, "attributes": { "title": "How are consumer behavior and marketing strategy researchers incorporating the SDGs? A review and opportunities for future research", "sourcetitle": "Australasian Marketing Journal", @@ -37772,7 +7297,7 @@ } }, { - "key": "85126732106", + "key": 85126732106, "attributes": { "title": "Re-imagining Marketing Scholarship in the era of the UN Sustainable Development Goals", "sourcetitle": "Australasian Marketing Journal", @@ -37790,7 +7315,7 @@ } }, { - "key": "85120848538", + "key": 85120848538, "attributes": { "title": "Brand Display Magnitudes and Young Children\u2019s Brand Recognition", "sourcetitle": "Australasian Marketing Journal", @@ -37808,7 +7333,7 @@ } }, { - "key": "85126797091", + "key": 85126797091, "attributes": { "title": "eHealth Services and SDG3: Increasing the Capacity of Care", "sourcetitle": "Australasian Marketing Journal", @@ -37826,7 +7351,7 @@ } }, { - "key": "85107494797", + "key": 85107494797, "attributes": { "title": "Algorithmic bias: review, synthesis, and future research directions", "sourcetitle": "European Journal of Information Systems", @@ -37844,7 +7369,7 @@ } }, { - "key": "85127758314", + "key": 85127758314, "attributes": { "title": "The Sustainability Pyramid: A Hierarchical Approach to Greater Sustainability and the United Nations Sustainable Development Goals With Implications for Marketing Theory, Practice, and Public Policy", "sourcetitle": "Australasian Marketing Journal", @@ -37862,7 +7387,7 @@ } }, { - "key": "85126916017", + "key": 85126916017, "attributes": { "title": "The Effect of Seeking Resource Diversity on Post-Alliance Innovation Outcomes", "sourcetitle": "Australasian Marketing Journal", @@ -37880,7 +7405,7 @@ } }, { - "key": "85130068930", + "key": 85130068930, "attributes": { "title": "Decolonising the Marketing Academy: An Indigenous M\u0101ori Perspective on Engagement, Methodologies and Practices", "sourcetitle": "Australasian Marketing Journal", @@ -37898,7 +7423,7 @@ } }, { - "key": "85125899586", + "key": 85125899586, "attributes": { "title": "An Indigenous Perspective of the Australasian Marketing Academy", "sourcetitle": "Australasian Marketing Journal", @@ -37916,7 +7441,7 @@ } }, { - "key": "85126790623", + "key": 85126790623, "attributes": { "title": "Disciplined Vision Casting: A Method for Exploring Possible Futures in the Era of the UN Sustainable Development Goals", "sourcetitle": "Australasian Marketing Journal", @@ -37934,7 +7459,7 @@ } }, { - "key": "85132047812", + "key": 85132047812, "attributes": { "title": "Can the Subaltern(s) Speak? Amplifying the Voices of Global South Scholars in the Australasian Marketing Academy", "sourcetitle": "Australasian Marketing Journal", @@ -37952,7 +7477,7 @@ } }, { - "key": "85083297855", + "key": 85083297855, "attributes": { "title": "Programmatic creative: AI can think but it cannot feel", "sourcetitle": "Australasian Marketing Journal", @@ -37970,7 +7495,7 @@ } }, { - "key": "85107795919", + "key": 85107795919, "attributes": { "title": "The Convergence of Sustainability and Marketing: Transforming Marketing to Respond to a New World", "sourcetitle": "Australasian Marketing Journal", @@ -37988,7 +7513,7 @@ } }, { - "key": "85129285156", + "key": 85129285156, "attributes": { "title": "Gender Equity in the Marketing Academy: From Performative to Institutional Allyship", "sourcetitle": "Australasian Marketing Journal", @@ -38006,7 +7531,7 @@ } }, { - "key": "85106372191", + "key": 85106372191, "attributes": { "title": "Forecasting Advertisement Effectiveness: Neuroscience and Data Envelopment Analysis", "sourcetitle": "Australasian Marketing Journal", @@ -38024,7 +7549,7 @@ } }, { - "key": "85120983789", + "key": 85120983789, "attributes": { "title": "How Does Service Climate Influence Hotel Employees\u2019 Brand Citizenship Behavior? A Social Exchange and Social Identity Perspective", "sourcetitle": "Australasian Marketing Journal", @@ -38042,7 +7567,7 @@ } }, { - "key": "85121453780", + "key": 85121453780, "attributes": { "title": "Exploring Gen Y Luxury Consumers\u2019 Webrooming Behavior: An Integrated Approach", "sourcetitle": "Australasian Marketing Journal", @@ -38060,13 +7585,8 @@ } }, { - "key": "85146302485", + "key": 85146302485, "attributes": { - "title": "What are Airbnb hosts advertising? 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df: DataFrame containing the data\n", + " - start_year: Optional, the starting year for filtering\n", + " - end_year: Optional, the ending year for filtering\n", + " \n", + " Returns:\n", + " - DataFrame with filtered data\n", + " \"\"\"\n", + " \n", + " # Replace 'NA' with numpy.nan and reassign the DataFrame\n", + " df = df.replace({'year': 'NA'}, np.nan)\n", + " \n", + " # Drop rows where 'year' is NaN\n", + " df = df.dropna(subset=['year'])\n", + " \n", + " # Convert the 'year' column to integer using .astype\n", + " df['year'] = df['year'].astype(int)\n", + " \n", + " # Filter the data based on the 'year' column only if start_year and end_year are provided\n", + " if start_year is not None and end_year is not None:\n", + " df = df[df['year'].between(start_year, end_year)]\n", + " \n", + " # Extract necessary columns for the citation network\n", + " citations_df = df[['citing_art', 'scopus_id', 'sourcetitle', 'title', 'citedby_count', 'citations_per_year' , 'author', 'year']]\n", + " \n", + " return citations_df\n", + "\n", + "# Using the function to get a->b standardized data for the citations networks below\n", + "citations_df_2022_2023 = get_citations_df(list_references_standardized, 2022, 2023)\n", + "citations_df_2018_2021 = get_citations_df(list_references_standardized, 2018, 2021)\n", + "citations_df_2013_2017 = get_citations_df(list_references_standardized, 2013, 2017)\n", + "citations_df_before_2013 = get_citations_df(list_references_standardized, 0, 2012)\n", + "citations_df_overall = get_citations_df(list_references_standardized) #No filter on years: " + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "id": "7528e411", + "metadata": {}, + "outputs": [], + "source": [ + "def standardize_values(df, groupby_column, value_column):\n", + " \"\"\"\n", + " Standardize the values of the specified column based on the most frequent non-empty value and fewest characters \n", + " within each group.\n", + "\n", + " Parameters:\n", + " - df: DataFrame\n", + " - groupby_column: The column by which we group data.\n", + " - value_column: The column whose values we want to standardize based on the rules.\n", + "\n", + " Returns:\n", + " - DataFrame with standardized values.\n", + " \"\"\"\n", + " \n", + " def custom_mode(series):\n", + " # Remove NA values and other representations of NA\n", + " series = series.dropna()\n", + " series = series[~series.isin(['', 'NA'])]\n", + " \n", + " # If all values were NA or empty\n", + " if series.empty:\n", + " return np.nan # Using numpy's nan for consistency\n", + "\n", + " # Get value counts\n", + " counts = series.value_counts()\n", + "\n", + " # If there's a single most common value, return it\n", + " if len(counts) == 1 or counts.iloc[0] != counts.iloc[1]:\n", + " return counts.idxmax()\n", + "\n", + " # If multiple values have the same max count, apply further rules\n", + " top_values = counts[counts == counts.iloc[0]].index.tolist()\n", + "\n", + " # Sort by fewest characters\n", + " sorted_by_chars = sorted(top_values, key=lambda x: len(x))\n", + "\n", + " # If there's a single value with the fewest characters, return it\n", + " if len(sorted_by_chars) == 1 or len(sorted_by_chars[0]) != len(sorted_by_chars[1]):\n", + " return sorted_by_chars[0]\n", + "\n", + " # If the column is not the author's name, apply the uppercase letter rule.\n", + " if value_column != \"author_name\": # adjust \"author_name\" to the correct column name if necessary\n", + " return sorted(sorted_by_chars, key=lambda x: sum(1 for c in x if c.isupper()), reverse=True)[0]\n", + " else:\n", + " return sorted_by_chars[0]\n", + "\n", + " # Find the most common value for each group based on the custom mode\n", + " most_common_value = df.groupby(groupby_column)[value_column].apply(custom_mode).to_dict()\n", + "\n", + " # Map the most common values to the dataframe based on the group\n", + " df[value_column] = df[groupby_column].map(most_common_value)\n", + "\n", + " return df\n", + "\n", + "\n", + "# Usage example:\n", + "list_references_standardized = standardize_values(list_references, 'scopus_id', 'title')\n", + "list_references_standardized = standardize_values(list_references_standardized, 'scopus_id', 'sourcetitle')\n", + "list_references_standardized = standardize_values(list_references_standardized, 'scopus_id', 'author')" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "id": "b4bce5b8", + "metadata": {}, + "outputs": [], + "source": [ + "def get_citations_df(df, start_year=None, end_year=None):\n", + " \"\"\"\n", + " Filter and extract necessary columns for citation network from a DataFrame based on a range of years.\n", + " \n", + " Parameters:\n", + " - df: DataFrame containing the data\n", + " - start_year: Optional, the starting year for filtering\n", + " - end_year: Optional, the ending year for filtering\n", + " \n", + " Returns:\n", + " - DataFrame with filtered data\n", + " \"\"\"\n", + " \n", + " # Replace 'NA' with numpy.nan and reassign the DataFrame\n", + " df = df.replace({'year': 'NA'}, np.nan)\n", + " \n", + " # Drop rows where 'year' is NaN\n", + " df = df.dropna(subset=['year'])\n", + " \n", + " # Convert the 'year' column to integer using .astype\n", + " df['year'] = df['year'].astype(int)\n", + " \n", + " # Filter the data based on the 'year' column only if start_year and end_year are provided\n", + " if start_year is not None and end_year is not None:\n", + " df = df[df['year'].between(start_year, end_year)]\n", + " \n", + " # Extract necessary columns for the citation network\n", + " citations_df = df[['citing_art', 'scopus_id', 'sourcetitle', 'title', 'citedby_count', 'citations_per_year' , 'author', 'year']]\n", + " \n", + " return citations_df\n", + "\n", + "# Using the function to get a->b standardized data for the citations networks below\n", + "citations_df_2022_2023 = get_citations_df(list_references_standardized, 2022, 2023)\n", + "citations_df_2018_2021 = get_citations_df(list_references_standardized, 2018, 2021)\n", + "citations_df_2013_2017 = get_citations_df(list_references_standardized, 2013, 2017)\n", + "citations_df_before_2013 = get_citations_df(list_references_standardized, 0, 2012)\n", + "citations_df_overall = get_citations_df(list_references_standardized) #No filter on years: " + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "id": "71ba97a2", + "metadata": {}, + "outputs": [], + "source": [ + "def get_info_references_dict(df, key, column):\n", + " \"\"\"\n", + " Create a dictionary with keys from the specified key_column and values from the specified value_column.\n", + "\n", + " :param df: Input DataFrame.\n", + " :param key_column: Column name to be used as keys in the resulting dictionary.\n", + " :param value_column: Column name to be used as values in the resulting dictionary.\n", + " :return: Dictionary with keys from key_column and values from value_column.\n", + " \"\"\"\n", + " if key not in df.columns or column not in df.columns:\n", + " raise ValueError(\"The required columns are not present in the DataFrame.\")\n", + " return sort_dict(df.set_index(key)[column].to_dict())\n", + " \n", + "\n", + "# We also need to get the info of the citing articles, otherwise we won't get any info when we click \n", + "# on the nodes and we will have the number of the node as node label instead of the author name\n", + "# Create the 'citing_art' column by stripping the first 10 characters from 'dc_identifier'\n", + "data['citing_art'] = data['dc_identifier'].str[10:]\n", + "\n", + "# Getting the current year\n", + "current_year = datetime.now().year\n", + "\n", + "# English Comment: Function to calculate citations per year, handles NaN values, division by zero, and the current year.\n", + "def calculate_citations_per_year(row):\n", + " if pd.isna(row['year']):\n", + " return np.nan\n", + " elif (current_year - row['year']) == 0:\n", + " return 0 # Handle division by zero by returning 0\n", + " else:\n", + " return round(row['citedby_count'] / (current_year - row['year']), 2)\n", + "\n", + "# Creating the new column 'citations_per_year'\n", + "data['citations_per_year'] = data.apply(calculate_citations_per_year, axis=1)\n", + "\n", + "# List of columns to use in the networks later as attributes. We can add more columns if we want to.\n", + "columns_to_extract = ['title', 'sourcetitle', 'citedby_count', 'author', 'year', 'citations_per_year']\n", + "\n", + "# Dictionary of dataframes with their respective names\n", + "dfs = {\n", + " \"2022_2023\": citations_df_2022_2023,\n", + " \"2018_2021\": citations_df_2018_2021,\n", + " \"2013_2017\": citations_df_2013_2017,\n", + " \"before_2013\": citations_df_before_2013,\n", + " \"overall\": citations_df_overall\n", + "}\n", + "\n", + "\n", + "# Map old column names to new column names\n", + "column_mapping = {\n", + " 'title': 'dc_title',\n", + " 'sourcetitle': 'prism_publicationName',\n", + " 'author': 'dc_creator',\n", + " 'year': 'year',\n", + " 'citations': 'citedby_count',\n", + " 'citations_per_year': 'citations_per_year'\n", + "}\n", + "\n", + "# Reverse mapping for merging\n", + "reverse_column_mapping = {v: k for k, v in column_mapping.items()}\n", + "\n", + "# Rename columns in data DataFrame for merging\n", + "data.rename(columns=reverse_column_mapping, inplace=True)\n", + "\n", + "\n", + "# Initialize the output dictionary\n", + "dict_references = {}\n", + "\n", + "# Retrieve the information for each period and each column\n", + "for period, df in dfs.items():\n", + " dict_references[period] = {}\n", + " for column in columns_to_extract:\n", + " # This check is important in case all columns are not present across all dataframes\n", + " if column in df.columns:\n", + " dict_references[period][column] = get_info_references_dict(df, 'scopus_id', column)\n", + "\n", + " # Get the citing_art dictionary from 'data' DataFrame\n", + " for column in columns_to_extract:\n", + " if column in data.columns:\n", + " citing_art_dict = get_info_references_dict(data, 'citing_art', column)\n", + " \n", + " # Add to dict_references only if key is not already present \n", + " # It means that the article in our data has been cited by others and is then already present in the references dataframe\n", + " for key, value in citing_art_dict.items():\n", + " if key not in dict_references[period].get(column, {}):\n", + " dict_references[period].setdefault(column, {})[key] = value\n" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "id": "fb80c28a", + "metadata": {}, + "outputs": [], + "source": [ + "def sigma_graph_references(dataframe, period_label):\n", + " \n", + " # Create a graph from the given dataframe\n", + " G = nx.from_pandas_edgelist(dataframe, 'citing_art', 'scopus_id', create_using=nx.DiGraph())\n", + " \n", + " # Fetch attributes for the given period from the global dict_references\n", + " attributes_dict = dict_references.get(period_label, {})\n", + "\n", + " # Set the attributes from dict_references to the nodes of the graph\n", + " for attribute, attribute_dict in attributes_dict.items():\n", + " nx.set_node_attributes(G, attribute_dict, name=attribute)\n", + "\n", + " # Set edge colors for visualization\n", + " for u, v in G.edges:\n", + " G[u][v][\"color\"] = \"#7D7C7C\"\n", + "\n", + " # Calculate the degree of each node\n", + " node_degree = dict(G.degree)\n", + "\n", + " # Compute multiple centrality metrics for nodes\n", + " node_degree_centrality = nx.degree_centrality(G)\n", + " node_degree_betweenness = nx.betweenness_centrality(G)\n", + " node_degree_closeness = nx.closeness_centrality(G)\n", + " node_degree_eigenvector = nx.closeness_centrality(G)\n", + " #node_degree_constraint_weighted = nx.constraint(G, weight=\"value\")\n", + " node_degree_constraint_unweighted = nx.constraint(G)\n", + " \n", + " # Set node attributes for various metrics\n", + " nx.set_node_attributes(G, node_degree_centrality, 'centrality')\n", + " nx.set_node_attributes(G, node_degree_betweenness, 'betweenness')\n", + " nx.set_node_attributes(G, node_degree_closeness, 'closeness')\n", + " nx.set_node_attributes(G, node_degree_eigenvector, 'eigenvector centrality')\n", + " #nx.set_node_attributes(G, node_degree_constraint_weighted, 'burt\\'s constraint weighted')\n", + " nx.set_node_attributes(G, node_degree_constraint_unweighted, 'burt constraint unweighted')\n", + " \n", + " # Set node attributes based on the selected 'year_period'\n", + " \n", + "\n", + " # Construct the sigma graph and customize visualization\n", + " Sigma.write_html(G,\n", + " default_edge_type = \"arrow\", # Set default edge type\n", + " fullscreen = True, # Display in fullscreen mode\n", + " label_density = 2, # Increase this to have more labels appear\n", + " label_font = \"Helvetica Neue\", # Set label font\n", + " max_categorical_colors = 30, # Max categorical colors for communities\n", + " node_border_color_from = 'node', # Set node border color from 'node' attribute\n", + " node_color = \"community\", # Set node colors\n", + " node_label = \"author\", # Set node label from 'author' attribute\n", + " node_label_size = G.in_degree, # Set node label size\n", + " node_label_size_range = (12, 36), # Set node label size range\n", + " node_metrics = {\"community\": {\"name\": \"louvain\", \"resolution\": 1}}, # Specify node metrics\n", + " node_size = G.in_degree, # Set node size based on the in_degree attribute\n", + " node_size_range = (3, 30), # Set node size range\n", + " path = f\"networks/references/{period_label}_sigma.html\", # Specify the output file path\n", + " start_layout = 10 # Start the layout algorithm automatically and lasts 5 seconds\n", + " #node_border_color = \"black\", # Set node border color\n", + " #edge_color = \"source\", # Set edge color from 'source' attribute\n", + " )\n", + "\n", + " return G" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "id": "3aa4f1dc", + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "Object of type builtin_function_or_method is not JSON serializable", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[93], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m G_2022_2023_references \u001b[38;5;241m=\u001b[39m sigma_graph_references(citations_df_2022_2023, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m2022_2023\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "Cell \u001b[1;32mIn[92], line 40\u001b[0m, in \u001b[0;36msigma_graph_references\u001b[1;34m(dataframe, period_label)\u001b[0m\n\u001b[0;32m 34\u001b[0m nx\u001b[38;5;241m.\u001b[39mset_node_attributes(G, node_degree_constraint_unweighted, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mburt constraint unweighted\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 36\u001b[0m \u001b[38;5;66;03m# Set node attributes based on the selected 'year_period'\u001b[39;00m\n\u001b[0;32m 37\u001b[0m \n\u001b[0;32m 38\u001b[0m \n\u001b[0;32m 39\u001b[0m \u001b[38;5;66;03m# Construct the sigma graph and customize visualization\u001b[39;00m\n\u001b[1;32m---> 40\u001b[0m Sigma\u001b[38;5;241m.\u001b[39mwrite_html(G,\n\u001b[0;32m 41\u001b[0m default_edge_type \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124marrow\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Set default edge type\u001b[39;00m\n\u001b[0;32m 42\u001b[0m fullscreen \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m, \u001b[38;5;66;03m# Display in fullscreen mode\u001b[39;00m\n\u001b[0;32m 43\u001b[0m label_density \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;66;03m# Increase this to have more labels appear\u001b[39;00m\n\u001b[0;32m 44\u001b[0m label_font \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mHelvetica Neue\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Set label font\u001b[39;00m\n\u001b[0;32m 45\u001b[0m max_categorical_colors \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m30\u001b[39m, \u001b[38;5;66;03m# Max categorical colors for communities\u001b[39;00m\n\u001b[0;32m 46\u001b[0m node_border_color_from \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnode\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;66;03m# Set node border color from 'node' attribute\u001b[39;00m\n\u001b[0;32m 47\u001b[0m node_color \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcommunity\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Set node colors\u001b[39;00m\n\u001b[0;32m 48\u001b[0m node_label \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mauthor\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Set node label from 'author' attribute\u001b[39;00m\n\u001b[0;32m 49\u001b[0m node_label_size \u001b[38;5;241m=\u001b[39m G\u001b[38;5;241m.\u001b[39min_degree, \u001b[38;5;66;03m# Set node label size\u001b[39;00m\n\u001b[0;32m 50\u001b[0m node_label_size_range \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m12\u001b[39m, \u001b[38;5;241m36\u001b[39m), \u001b[38;5;66;03m# Set node label size range\u001b[39;00m\n\u001b[0;32m 51\u001b[0m node_metrics \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcommunity\u001b[39m\u001b[38;5;124m\"\u001b[39m: {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlouvain\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresolution\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;241m1\u001b[39m}}, \u001b[38;5;66;03m# Specify node metrics\u001b[39;00m\n\u001b[0;32m 52\u001b[0m node_size \u001b[38;5;241m=\u001b[39m G\u001b[38;5;241m.\u001b[39min_degree, \u001b[38;5;66;03m# Set node size based on the in_degree attribute\u001b[39;00m\n\u001b[0;32m 53\u001b[0m node_size_range \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m3\u001b[39m, \u001b[38;5;241m30\u001b[39m), \u001b[38;5;66;03m# Set node size range\u001b[39;00m\n\u001b[0;32m 54\u001b[0m path \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnetworks/references/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mperiod_label\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_sigma.html\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;66;03m# Specify the output file path\u001b[39;00m\n\u001b[0;32m 55\u001b[0m start_layout \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m10\u001b[39m \u001b[38;5;66;03m# Start the layout algorithm automatically and lasts 5 seconds\u001b[39;00m\n\u001b[0;32m 56\u001b[0m \u001b[38;5;66;03m#node_border_color = \"black\", # Set node border color\u001b[39;00m\n\u001b[0;32m 57\u001b[0m \u001b[38;5;66;03m#edge_color = \"source\", # Set edge color from 'source' attribute\u001b[39;00m\n\u001b[0;32m 58\u001b[0m )\n\u001b[0;32m 60\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m G\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\ipysigma\\sigma.py:1143\u001b[0m, in \u001b[0;36mSigma.write_html\u001b[1;34m(cls, graph, path, fullscreen, **kwargs)\u001b[0m\n\u001b[0;32m 1140\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mheight\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 1141\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mraw_height\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcalc(100vh - 16px)\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m-> 1143\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(graph, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\u001b[38;5;241m.\u001b[39mto_html(path)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\ipysigma\\sigma.py:1133\u001b[0m, in \u001b[0;36mSigma.to_html\u001b[1;34m(self, path)\u001b[0m\n\u001b[0;32m 1130\u001b[0m current_snapshot \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msnapshot\n\u001b[0;32m 1131\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msnapshot \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m-> 1133\u001b[0m embed_minimal_html(path, views\u001b[38;5;241m=\u001b[39m[\u001b[38;5;28mself\u001b[39m])\n\u001b[0;32m 1135\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msnapshot \u001b[38;5;241m=\u001b[39m current_snapshot\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\ipywidgets\\embed.py:302\u001b[0m, in \u001b[0;36membed_minimal_html\u001b[1;34m(fp, views, title, template, **kwargs)\u001b[0m\n\u001b[0;32m 286\u001b[0m \u001b[38;5;129m@doc_subst\u001b[39m(_doc_snippets)\n\u001b[0;32m 287\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21membed_minimal_html\u001b[39m(fp, views, title\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mIPyWidget export\u001b[39m\u001b[38;5;124m'\u001b[39m, template\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 288\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Write a minimal HTML file with widget views embedded.\u001b[39;00m\n\u001b[0;32m 289\u001b[0m \n\u001b[0;32m 290\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 300\u001b[0m \u001b[38;5;124;03m {embed_kwargs}\u001b[39;00m\n\u001b[0;32m 301\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 302\u001b[0m snippet \u001b[38;5;241m=\u001b[39m embed_snippet(views, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m 304\u001b[0m values \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 305\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtitle\u001b[39m\u001b[38;5;124m'\u001b[39m: title,\n\u001b[0;32m 306\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msnippet\u001b[39m\u001b[38;5;124m'\u001b[39m: snippet,\n\u001b[0;32m 307\u001b[0m }\n\u001b[0;32m 308\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m template \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\ipywidgets\\embed.py:279\u001b[0m, in \u001b[0;36membed_snippet\u001b[1;34m(views, drop_defaults, state, indent, embed_url, requirejs, cors)\u001b[0m\n\u001b[0;32m 274\u001b[0m load \u001b[38;5;241m=\u001b[39m load_requirejs_template \u001b[38;5;28;01mif\u001b[39;00m requirejs \u001b[38;5;28;01melse\u001b[39;00m load_template\n\u001b[0;32m 276\u001b[0m use_cors \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m crossorigin=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124manonymous\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m cors \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m 277\u001b[0m values \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 278\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mload\u001b[39m\u001b[38;5;124m'\u001b[39m: load\u001b[38;5;241m.\u001b[39mformat(embed_url\u001b[38;5;241m=\u001b[39membed_url, use_cors\u001b[38;5;241m=\u001b[39muse_cors),\n\u001b[1;32m--> 279\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mjson_data\u001b[39m\u001b[38;5;124m'\u001b[39m: escape_script(json\u001b[38;5;241m.\u001b[39mdumps(data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmanager_state\u001b[39m\u001b[38;5;124m'\u001b[39m], indent\u001b[38;5;241m=\u001b[39mindent)),\n\u001b[0;32m 280\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mwidget_views\u001b[39m\u001b[38;5;124m'\u001b[39m: widget_views,\n\u001b[0;32m 281\u001b[0m }\n\u001b[0;32m 283\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m snippet_template\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mvalues)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\__init__.py:238\u001b[0m, in \u001b[0;36mdumps\u001b[1;34m(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)\u001b[0m\n\u001b[0;32m 232\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 233\u001b[0m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;241m=\u001b[39m JSONEncoder\n\u001b[0;32m 234\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(\n\u001b[0;32m 235\u001b[0m skipkeys\u001b[38;5;241m=\u001b[39mskipkeys, ensure_ascii\u001b[38;5;241m=\u001b[39mensure_ascii,\n\u001b[0;32m 236\u001b[0m check_circular\u001b[38;5;241m=\u001b[39mcheck_circular, allow_nan\u001b[38;5;241m=\u001b[39mallow_nan, indent\u001b[38;5;241m=\u001b[39mindent,\n\u001b[0;32m 237\u001b[0m separators\u001b[38;5;241m=\u001b[39mseparators, default\u001b[38;5;241m=\u001b[39mdefault, sort_keys\u001b[38;5;241m=\u001b[39msort_keys,\n\u001b[1;32m--> 238\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkw)\u001b[38;5;241m.\u001b[39mencode(obj)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:202\u001b[0m, in \u001b[0;36mJSONEncoder.encode\u001b[1;34m(self, o)\u001b[0m\n\u001b[0;32m 200\u001b[0m chunks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39miterencode(o, _one_shot\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m 201\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(chunks, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m)):\n\u001b[1;32m--> 202\u001b[0m chunks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(chunks)\n\u001b[0;32m 203\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(chunks)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:432\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode\u001b[1;34m(o, _current_indent_level)\u001b[0m\n\u001b[0;32m 430\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m _iterencode_list(o, _current_indent_level)\n\u001b[0;32m 431\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(o, \u001b[38;5;28mdict\u001b[39m):\n\u001b[1;32m--> 432\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m _iterencode_dict(o, _current_indent_level)\n\u001b[0;32m 433\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 434\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m markers \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:406\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode_dict\u001b[1;34m(dct, _current_indent_level)\u001b[0m\n\u001b[0;32m 404\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 405\u001b[0m chunks \u001b[38;5;241m=\u001b[39m _iterencode(value, _current_indent_level)\n\u001b[1;32m--> 406\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m chunks\n\u001b[0;32m 407\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m newline_indent \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 408\u001b[0m _current_indent_level \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:406\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode_dict\u001b[1;34m(dct, _current_indent_level)\u001b[0m\n\u001b[0;32m 404\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 405\u001b[0m chunks \u001b[38;5;241m=\u001b[39m _iterencode(value, _current_indent_level)\n\u001b[1;32m--> 406\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m chunks\n\u001b[0;32m 407\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m newline_indent \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 408\u001b[0m _current_indent_level \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n", + " \u001b[1;31m[... skipping similar frames: _make_iterencode.._iterencode_dict at line 406 (2 times)]\u001b[0m\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:406\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode_dict\u001b[1;34m(dct, _current_indent_level)\u001b[0m\n\u001b[0;32m 404\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 405\u001b[0m chunks \u001b[38;5;241m=\u001b[39m _iterencode(value, _current_indent_level)\n\u001b[1;32m--> 406\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m chunks\n\u001b[0;32m 407\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m newline_indent \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 408\u001b[0m _current_indent_level \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:439\u001b[0m, in \u001b[0;36m_make_iterencode.._iterencode\u001b[1;34m(o, _current_indent_level)\u001b[0m\n\u001b[0;32m 437\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCircular reference detected\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 438\u001b[0m markers[markerid] \u001b[38;5;241m=\u001b[39m o\n\u001b[1;32m--> 439\u001b[0m o \u001b[38;5;241m=\u001b[39m _default(o)\n\u001b[0;32m 440\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m _iterencode(o, _current_indent_level)\n\u001b[0;32m 441\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m markers \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\json\\encoder.py:180\u001b[0m, in \u001b[0;36mJSONEncoder.default\u001b[1;34m(self, o)\u001b[0m\n\u001b[0;32m 161\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdefault\u001b[39m(\u001b[38;5;28mself\u001b[39m, o):\n\u001b[0;32m 162\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Implement this method in a subclass such that it returns\u001b[39;00m\n\u001b[0;32m 163\u001b[0m \u001b[38;5;124;03m a serializable object for ``o``, or calls the base implementation\u001b[39;00m\n\u001b[0;32m 164\u001b[0m \u001b[38;5;124;03m (to raise a ``TypeError``).\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 178\u001b[0m \n\u001b[0;32m 179\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 180\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mObject of type \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mo\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m 181\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mis not JSON serializable\u001b[39m\u001b[38;5;124m'\u001b[39m)\n", + "\u001b[1;31mTypeError\u001b[0m: Object of type builtin_function_or_method is not JSON serializable" + ] + } + ], + "source": [ + "G_2022_2023_references = sigma_graph_references(citations_df_2022_2023, \"2022_2023\")" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "id": "830f312c", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b43846c91027406587cff7688557c7ce", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(HBox(children=(Sigma(nx.DiGraph with 526 nodes and 469 edges), Sigma(nx.DiGraph with 526 nodes …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "SigmaGrid(G_2022_2023_references,\n", + " views=[{'node_size': G_2022_2023_references.in_degree}, {'node_size': \"centrality\"}],\n", + " #path=\"networks/references/2022_2023_sigma_grid.html\"\n", + " default_edge_type = \"arrow\", # Set default edge type # Display in fullscreen mode\n", + " label_density = 1, # Increase this to have more labels appear\n", + " label_font = \"Helvetica Neue\", # Set label font\n", + " max_categorical_colors = 30, # Max categorical colors for communities\n", + " node_border_color_from = 'node', # Set node border color from 'node' attribute\n", + " node_color = \"community\", # Set node colors\n", + " node_label = \"author\", # Set node label from 'author' attribute # Set node label size\n", + " node_label_size_range = (12, 36), # Set node label size range\n", + " node_metrics = {\"community\": {\"name\": \"louvain\", \"resolution\": 1}}, # Specify node metrics # Set node size based on the in_degree attribute\n", + " node_size_range = (3, 30), # Set node size range\n", + " #path = \"networks/references/2022_2023_sigma_grid.html\", # Specify the output file path\n", + " start_layout = 10 # Start the layout algorithm automatically and lasts 5 seconds\n", + " #node_border_color = \"black\", # Set node border color\n", + " #edge_color = \"source\",\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ac35748e", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ebd294c2", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}