The purpose of this project is to analyze the emoji usage patterns among various demographics, such as user age and gender, and social media platforms. By visualizing this data, the report seeks to reveal insights into which emojis are most popular, how different user groups use emojis (i.e., which platform they are used on), and the context or reasons behind their usage.
This project gives insight into emoji usage across different demographics. As emojis continue to be used in digital communication to express user emotions and convey user messages, the project aims to uncover trends and preferences in emoji usage. This report may be valuable for those in social media marketing and analysis or app development.
The dataset used in this project was downloaded from Kaggle (https://www.kaggle.com/datasets/waqi786/emoji-trends-dataset). The CSV file consists of anonymized data showing emoji usage by users across different social media platforms and demographics (age and gender). The key attributes in the dataset include the emoji used, the user's age and gender, the platform in which the emoji was used on, and the user's reason for using the emoji.
The data was cleaned using ETL (extract, transform, and load) processes. I extracted the data set from Kaggle via a CSV file, transformed the data using Power BI's query editor, and loaded the cleaned and transformed data into Power BI's data model for analysis and visualization. To clean the data (within the Power BI query editor) I filtered out any missing or incomplete records, renamed the columns for clarity, wrote a script in which to categorize the user ages into specific groups (i.e., Teenages 13-18, Young Adults 19-24), and removed unnecessary columns.
Emoji (Emoji used), Age: (User age), Gender: (User gender such as male or female), Age Group: (User age group such as Teenagers 13-18, etc.,), Platform: (Social media platform where emoji was used), Reason: (Reason for using emoji such as love, confusion, celebration, etc.,).
The analysis performed included counting the total amount of times each emoji was used, breaking down emoji usage by user gender and age group, and analyzing the various reasons for emoji usage. The platform distribution was also examined to see where different emojis were most frequently used.
Bar Charts: Display the most used emojis and their usage by gender Clustered Column Charts: Analyze emoji usage by age group Pie Charts: Examine the distribution of emoji usage by platform and the reasons for emoji usage by gender KPI Visuals: Highlight the total emoji usage count
The analysis revealed that certain emojis are universally popular across all demographics, while others are more commonly used by specific age groups or genders. For example, the report showed that at the time of this anonymous survey, Twitter was the most popular platform for emoji usage. Additionally, the analysis revealed how certain emojis are used in different contexts such as love or humor. Understanding the reasons for emoji usage can offer insight into how emojis convey emotions or enhance digital communication.
What makes my report interactive is the inclusion of slicers which allow users to filter through the data by specific emojis, age groups, social media platforms, etc., The charts update dynamically based on the selections, providing a tailored view of the data. This interactivity allows the reoort's viewer to explore the data in a way that suits their specific needs.
Users can interact with the report by selecting different emojis, age groups, or platforms from the slicers. Seleting something from the report will automatically update its visuals to reflect the selected criteria.
This project was mainly created using Microsoft Power BI. The data was collected from Kaggle.com, cleaned, transformed, and loaded using Power BI's Power BI Power Query, and visualized using a mixture of tools within Power BI and Microsoft PowerPoint. Microsoft PowerPoint allowed me the freedom and flexibility to create a more aesthetically pleasing user interface.
This report concludes through analysis and visualizations that emoji usage is highly influenced by age, gender, and social media platform. This insight could be valuable for those looking to understand digital communication trends.
Future improvements in this project could include analyzing specific emoji trends over time (dates and/or times of usage would be needed for this analysis) or analyzing emoji usage based on additional demographic factors such as a user's geographic location.
This report can be viewed by downloading the Power BI file directly from GitHub and opening it within Power BI Desktop.
This project was completed independently in an effort to gain more experience with data analysis, data visualization, and Microsoft Power BI, but I would like to acknowledge the Power BI community forums for their useful tips and support during the development process!
For any questions or collaboration opportunities, you can feel free to reach me via my GitHub profile at [KatGilliland]. I am extremely open to discussing this project or exploring new data analysis challenges.