9_Journals_additional_info
zuzannazagrodzka
2023-12-04
Last updated: 2023-12-20
Checks: 7 0
Knit directory:
workflowr-policy-landscape/
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Additional information about journals (not included in the manuscript)
This script creates a figure showing how many journals per category (for-profit OA, for-profit noOA, not-for-profit OA and not-for-profit noOA) are owned by the societies, different institutions (other) or solely by publishers.
# Clearing R
rm(list=ls())
# Loading libraries
# Libraries used for text/data analysis
library(tidyverse)
library(dplyr)
library(tidytext)
# Libraries used to create plots
library(ggplot2)
library(RColorBrewer)
# Library to create a table when converting to html
library("kableExtra")
# Library to read an arrow file
library(arrow)Importing data
# Importing dataset that we originally created and used in our analysis
df_corpuses <- read_feather(file = "./data/original_dataset_reproducibility_check/original_cleaned_data.arrow")Adding a column profit and access
Adding column based on the name of the journal if its OA run by for profit or not-for-profit:
for_profit_no_oa: “BioSciences”, “Biological Conservation”, “Conservation Biology”, “Ecological Applications”,“Ecology Letters”, “Ecology”, “Frontiers in Ecology and the Environment”, “Global Change Biology”, “Journal of Applied Ecology”, “Nature Ecology and Evolution”, “Trends in Ecology & Evolution”
no_profit_no_oa: “American Naturalist”, “Annual Review of Ecology Evolution and Systematics”, “Evolution”, “Philosophical Transactions of the Royal Society B”, “Proceedings of the Royal Society B Biological Sciences”
for_profit_oa: “Arctic, Antarctic, and Alpine Research”, “Biogeosciences”, “Conservation Letters”, “Diversity and Distributions”, “Ecology and Evolution”, “Evolutionary Applications”, “Neobiota”, “PeerJJournal”
no_profit_oa: “Ecology and Society”, “Evolution Letters”, “Frontiers in Ecology and Evolution”, “Plos Biology”, “Remote Sensing in Ecology and Conservation”, “eLifeJournal”
Data Prep and Cleaning
# Data preparation
## Getting a data set with the words
data_journals <- df_corpuses
dim(data_journals)[1] 22822 10colnames(data_journals) [1] "txt" "filename" "name" "doc_type"
[5] "stakeholder" "sentence_doc" "orig_word" "word_mix"
[9] "word" "org_subgroups"unique(data_journals$org_subgroups)[1] "advocates" "funders" "journals_nonOA"
[4] "journals_OA" "publishers_nonProfit" "publishers_Profit"
[7] "repositories" "societies" # Merging and removing duplicates
data_journals <- data_journals %>%
rename(document = name) %>%
select(document, org_subgroups) %>%
distinct(document, .keep_all = TRUE) %>%
filter(org_subgroups %in% c("journals_nonOA", "journals_OA")) %>%
rename(access = org_subgroups)
data <- data_journals
# Adding a column with a new variable "profit access"
data$profit_access <- data$document
data$profit_access[data$profit_access%in% c("BioSciences", "Biological Conservation", "Conservation Biology", "Ecological Applications","Ecology Letters", "Ecology", "Frontiers in Ecology and the Environment", "Global Change Biology", "Journal of Applied Ecology", "Nature Ecology and Evolution", "Trends in Ecology & Evolution")] <- "for_profit_no_oa"
data$profit_access[data$profit_access%in% c("American Naturalist", "Annual Review of Ecology Evolution and Systematics", "Evolution", "Philosophical Transactions of the Royal Society B", "Proceedings of the Royal Society B Biological Sciences")] <- "no_profit_no_oa"
data$profit_access[data$profit_access%in% c("Arctic, Antarctic, and Alpine Research", "Biogeosciences", "Conservation Letters", "Diversity and Distributions", "Ecology and Evolution", "Evolutionary Applications", "Neobiota", "PeerJJournal")] <- "for_profit_oa"
data$profit_access[data$profit_access%in% c("Ecology and Society", "Evolution Letters", "Frontiers in Ecology and Evolution", "Plos Biology", "Remote Sensing in Ecology and Conservation", "eLifeJournal")] <- "no_profit_oa"
check <- data
check <- check %>%
select(profit_access) %>%
group_by_all() %>%
summarise(COUNT = n())
check# A tibble: 4 × 2
profit_access COUNT
<chr> <int>
1 for_profit_no_oa 11
2 for_profit_oa 8
3 no_profit_no_oa 5
4 no_profit_oa 6data_journals <- data
# Adding a column "profit"
data$profit <- data$profit_access
data$profit[data$profit_access%in% c("for_profit_no_oa", "for_profit_oa")] <- "profit"
data$profit[data$profit_access%in% c("no_profit_no_oa", "no_profit_oa")] <- "no_profit"
# # Check that all rows were replaced
check <- data
check <- check %>%
select(profit) %>%
group_by_all() %>%
summarise(COUNT = n())
check# A tibble: 2 × 2
profit COUNT
<chr> <int>
1 no_profit 11
2 profit 19data_journals <- data# Adding a column with a new variable "society_journal" that tells us if the journal is run by societies/other organisations or just by publisher
data <- data_journals
data$society_journal <- data$document
data$society_journal[data$society_journal%in% c("BioSciences", "Conservation Biology", "Ecological Applications", "Ecology", "Frontiers in Ecology and the Environment", "Journal of Applied Ecology", "American Naturalist", "Evolution", "Philosophical Transactions of the Royal Society B", "Proceedings of the Royal Society B Biological Sciences", "Conservation Letters", "Ecology and Evolution", "Evolution Letters", "Remote Sensing in Ecology and Conservation")] <- "yes"
data$society_journal[data$society_journal%in% c("Biological Conservation", "Global Change Biology", "Nature Ecology and Evolution", "Trends in Ecology & Evolution", "Annual Review of Ecology Evolution and Systematics", "Diversity and Distributions", "Evolutionary Applications", "PeerJJournal", "Ecology and Society", "Frontiers in Ecology and Evolution", "Plos Biology", "eLifeJournal")] <- "no"
data$society_journal[data$society_journal%in% c("Ecology Letters", "Arctic, Antarctic, and Alpine Research", "Biogeosciences", "Neobiota")] <- "other"
# Check that all rows were replaced
check <- data
check <- check %>%
select(society_journal) %>%
group_by_all() %>%
summarise(COUNT = n())
check# A tibble: 3 × 2
society_journal COUNT
<chr> <int>
1 no 12
2 other 4
3 yes 14data_journals <- data# Data prep for the figure
head(data_journals)# A tibble: 6 × 5
document access profit_access profit society_journal
<chr> <chr> <chr> <chr> <chr>
1 American Naturalist journ… no_profit_no… no_pr… yes
2 Annual Review of Ecology Evolutio… journ… no_profit_no… no_pr… no
3 Biological Conservation journ… for_profit_n… profit no
4 BioSciences journ… for_profit_n… profit yes
5 Conservation Biology journ… for_profit_n… profit yes
6 Ecological Applications journ… for_profit_n… profit yes # calculate percentages, put into dataframe
df <- data_journals %>%
mutate(access = factor(access)) %>%
mutate(profit_access = factor(profit_access)) %>%
mutate(profit = factor(profit)) %>%
mutate(society_journal = factor(society_journal)) %>%
group_by(profit_access, society_journal) %>%
summarize(n = n()) %>%
mutate(freq = n / sum(n))`summarise()` has grouped output by 'profit_access'. You can override using the
`.groups` argument.df# A tibble: 10 × 4
# Groups: profit_access [4]
profit_access society_journal n freq
<fct> <fct> <int> <dbl>
1 for_profit_no_oa no 4 0.364
2 for_profit_no_oa other 1 0.0909
3 for_profit_no_oa yes 6 0.545
4 for_profit_oa no 3 0.375
5 for_profit_oa other 3 0.375
6 for_profit_oa yes 2 0.25
7 no_profit_no_oa no 1 0.2
8 no_profit_no_oa yes 4 0.8
9 no_profit_oa no 4 0.667
10 no_profit_oa yes 2 0.333 Creating a figure
legend_title <- "Society owned"
ggplot(df, aes(x = profit_access, y = n, fill = society_journal)) +
geom_bar(stat='identity') +
theme_bw() +
theme(panel.border = element_blank(), panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), axis.line = element_line(colour = "black")) +
scale_fill_manual(legend_title, values=c("#999999", "#E69F00", "#56B4E9")) + #no, other, yes
scale_x_discrete(limit = c("for_profit_no_oa", "for_profit_oa", "no_profit_no_oa", "no_profit_oa"),
labels = c("For-profit nonOA","For-profit OA","Non-profit nonOA", "Non-profit OA")) +
labs(y= "Frequency", x = "Journal category")
sessionInfo()R version 4.3.1 (2023-06-16)
Platform: x86_64-apple-darwin20 (64-bit)
Running under: macOS Monterey 12.6
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/London
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] arrow_13.0.0.1 kableExtra_1.3.4 RColorBrewer_1.1-3 tidytext_0.4.1
[5] lubridate_1.9.3 forcats_1.0.0 stringr_1.5.0 dplyr_1.1.3
[9] purrr_1.0.2 readr_2.1.4 tidyr_1.3.0 tibble_3.2.1
[13] ggplot2_3.4.3 tidyverse_2.0.0 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] gtable_0.3.4 xfun_0.40 bslib_0.5.1 processx_3.8.2
[5] lattice_0.21-8 callr_3.7.3 tzdb_0.4.0 vctrs_0.6.3
[9] tools_4.3.1 ps_1.7.5 generics_0.1.3 fansi_1.0.4
[13] janeaustenr_1.0.0 pkgconfig_2.0.3 tokenizers_0.3.0 Matrix_1.5-4.1
[17] assertthat_0.2.1 webshot_0.5.5 lifecycle_1.0.3 farver_2.1.1
[21] compiler_4.3.1 git2r_0.32.0 munsell_0.5.0 getPass_0.2-2
[25] httpuv_1.6.11 htmltools_0.5.6 SnowballC_0.7.1 sass_0.4.7
[29] yaml_2.3.7 later_1.3.1 pillar_1.9.0 jquerylib_0.1.4
[33] whisker_0.4.1 cachem_1.0.8 tidyselect_1.2.0 rvest_1.0.3
[37] digest_0.6.33 stringi_1.7.12 labeling_0.4.3 rprojroot_2.0.3
[41] fastmap_1.1.1 grid_4.3.1 colorspace_2.1-0 cli_3.6.1
[45] magrittr_2.0.3 utf8_1.2.3 withr_2.5.1 scales_1.2.1
[49] promises_1.2.1 bit64_4.0.5 timechange_0.2.0 rmarkdown_2.25
[53] httr_1.4.7 bit_4.0.5 hms_1.1.3 evaluate_0.21
[57] knitr_1.44 viridisLite_0.4.2 rlang_1.1.1 Rcpp_1.0.11
[61] glue_1.6.2 xml2_1.3.5 svglite_2.1.2 rstudioapi_0.15.0
[65] jsonlite_1.8.7 R6_2.5.1 systemfonts_1.0.4 fs_1.6.3