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njahn82 committed Jan 20, 2021
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47 changes: 18 additions & 29 deletions README.md
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Expand Up @@ -253,7 +253,6 @@ oa_df <- roadoi::oadoi_fetch(random_dois,

#### Analysis

<<<<<<< HEAD
roadoi returns the data in a consistent structure improved for further analysis in R.


Expand All @@ -263,14 +262,14 @@ oa_df
#> doi best_oa_location oa_locations oa_locations_em… data_standard is_oa
#> <chr> <list> <list> <list> <int> <lgl>
#> 1 10.1… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 2 10.1… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 3 10.1… <tibble [1 × 9]> <tibble [2 … <tibble [0 × 0]> 2 TRUE
#> 2 10.1… <tibble [1 × 8]> <tibble [1 … <tibble [0 × 0]> 2 TRUE
#> 3 10.1… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 4 10.1… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 5 10.1… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 5 10.7… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 6 10.1… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 7 10.1… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 8 10.1… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 9 10.3… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> 8 10.1… <tibble [1 × 8]> <tibble [1 … <tibble [0 × 0]> 2 TRUE
#> 9 10.1… <tibble [1 × 9]> <tibble [1 … <tibble [0 × 0]> 2 TRUE
#> 10 10.1… <tibble [0 × 0]> <tibble [0 … <tibble [0 × 0]> 2 FALSE
#> # … with 40 more rows, and 15 more variables: is_paratext <lgl>, genre <chr>,
#> # oa_status <chr>, has_repository_copy <lgl>, journal_is_oa <lgl>,
Expand All @@ -283,23 +282,16 @@ For example, to determine how many full-text links were found and which sources


```r
=======
roadoi returns the data in a consistent structure improved for further analysis in R. For example, to determine how many full-text links were found and which sources were used:
#> Error: <text>:1:1: Unerwartete(s) '=='
#> 1: ==
#> ^
```

```r
>>>>>>> 70e7915333d1bc2b210427025ce2d0709f7fd739
oa_df %>%
group_by(is_oa) %>%
summarise(Articles = n()) %>%
mutate(Proportion = Articles / sum(Articles)) %>%
arrange(desc(Articles))
#> Error: <text>:1:1: Unerwartete(s) '>'
#> 1: >
#> ^
#> # A tibble: 2 x 3
#> is_oa Articles Proportion
#> <lgl> <int> <dbl>
#> 1 FALSE 38 0.76
#> 2 TRUE 12 0.24
```

How did Unpaywall find those Open Access full-texts, which were characterized as best matches, and how are these OA types distributed over publication types?
Expand All @@ -313,19 +305,16 @@ oa_df %>%
group_by(oa_status, evidence, genre) %>%
summarise(Articles = n()) %>%
arrange(desc(Articles))
#> # A tibble: 9 x 4
#> # Groups: oa_status, evidence [9]
#> # A tibble: 6 x 4
#> # Groups: oa_status, evidence [5]
#> oa_status evidence genre Articles
#> <chr> <chr> <chr> <int>
#> 1 gold open (via page says license) journal-article 4
#> 2 bronze open (via free pdf) journal-article 2
#> 3 green oa repository (via OAI-PMH doi match) journal-article 2
#> 4 hybrid open (via crossref license) journal-article 2
#> 5 gold oa journal (via observed oa rate) journal-article 1
#> 6 gold oa journal (via publisher name) component 1
#> 7 gold open (via free pdf) journal-article 1
#> 8 green oa repository (semantic scholar lookup) book 1
#> 9 hybrid open (via page says license) journal-article 1
#> 1 bronze open (via free pdf) journal-article 6
#> 2 gold open (via page says license) journal-article 2
#> 3 gold oa journal (via publisher name) component 1
#> 4 green oa repository (semantic scholar lookup) journal-article 1
#> 5 green oa repository (semantic scholar lookup) monograph 1
#> 6 hybrid open (via page says license) journal-article 1
```

#### More examples
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6 changes: 0 additions & 6 deletions vignettes/intro.Rmd
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Expand Up @@ -152,7 +152,6 @@ oa_df <- roadoi::oadoi_fetch(random_dois,

#### Analysis

<<<<<<< HEAD
roadoi returns the data in a consistent structure improved for further analysis in R.

```{r}
Expand All @@ -162,11 +161,6 @@ oa_df
For example, to determine how many full-text links were found and which sources were used:

```{r}
=======
roadoi returns the data in a consistent structure improved for further analysis in R. For example, to determine how many full-text links were found and which sources were used:
```{r}
>>>>>>> 70e7915333d1bc2b210427025ce2d0709f7fd739
oa_df %>%
group_by(is_oa) %>%
summarise(Articles = n()) %>%
Expand Down

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