polisci_turnaround_acceptance

# load libraries -------------------------------------------------------

library(tidyverse)
library(rvest)
library(robotstxt)


# get journal names and links from my website -----------------------------

# get names
journal_names <-
  read_html("https://resulumit.com/blog/polisci-turnaround-acceptance/") |>
  html_elements(".table-striped a") |>
  html_text()

# get links
journal_urls <-
  read_html("https://resulumit.com/blog/polisci-turnaround-acceptance/") |>
  html_elements(".table-striped a") |>
  html_attr("href")

# merge and extract journal id
journals_df <- data.frame(journal_names, journal_urls) |>
  mutate(id = str_split(journal_urls, fixed("/"), simplify = TRUE)[, 4])


# check if scraping metrics is allowed [it is] -------------------------

robotstxt(domain = "https://www.tandfonline.com")$permissions


# scrape related pages for metrics --------------------------------------

temp_list <- list()

for (i in 1:nrow(journals_df)) {
  metrics_url = paste0(
    "https://www.tandfonline.com/action/journalInformation?show=journalMetrics&journalCode=",
    journals_df$id[i]
  )
  
  html <- read_html(metrics_url)
  
  try(foo <- tibble(
    journal = journals_df$journal_names[i],
    url = journals_df$journal_urls[i],
    metrics = html |>
      html_elements(".speed li") |>
      html_text()
  ),
  silent = TRUE)
  
  temp_list[[i]] <- foo
  
}


# create the metrics dataframe ------------------------------------------

df <- as_tibble(do.call(rbind, temp_list)) |>
  mutate(
    Journal = paste0("<a href='", url, "'>", journal, "</a>"),
    statistic = word(metrics, 1),
    type = case_when(
      str_detect(metrics, "acceptance rate") ~ "acceptance_rate",
      str_detect(metrics, "first decision") ~ "first_decision",
      str_detect(metrics, "post-review") ~ "first_review",
      str_detect(metrics, "online publication") ~ "online_publication"
    )
  ) |>
  pivot_wider(id_cols = "journal",
              names_from = "type",
              values_from = "statistic")


# plot turnaround statistics ----------------------------------------------

df |> select(-acceptance_rate) |>
  pivot_longer(
    cols = first_decision:online_publication,
    names_to = "type",
    values_to = "statistic"
  ) |>
  mutate(statistic = as.numeric(statistic),
         type = factor(
           type,
           levels = c("first_decision", "first_review", "online_publication"),
           labels = c(
             "Including desk rejects",
             "Excluding desk rejects",
             "Acceptance to online"
           )
         )) |>
  ggplot(aes(x = statistic, color = type, fill = type)) +
  geom_density(alpha = 0.3) +
  theme_light() +
  labs(y = "Density\n", x = "\nMedian number of days") +
  theme(
    panel.background = element_rect(fill = "#faf9f9"),
    plot.background = element_rect(fill = "#faf9f9"),
    legend.background = element_rect(fill = "#faf9f9"),
    axis.line = element_line(colour = "black", size = 0.25),
    panel.grid.major = element_line(colour = "grey95", size = 0.25),
    panel.grid.minor = element_line(colour = "grey95", size = 0.125),
    panel.border = element_rect(
      fill = NA,
      colour = "grey95",
      size = 0.25
    ),
    legend.position = "bottom",
    legend.title = element_blank()
  ) +
  scale_fill_discrete(name = "") +
  scale_color_discrete(name = "")


# plot acceptance rate ----------------------------------------------------

df |> mutate(acceptance_rate = as.numeric(str_remove(acceptance_rate, "%"))) |>
  ggplot(aes(x = acceptance_rate)) +
  geom_density(alpha = 0.3) +
  theme_light() +
  labs(y = "Density\n", x = "\nAcceptance Rate") +
  theme(
    panel.background = element_rect(fill = "#faf9f9"),
    plot.background = element_rect(fill = "#faf9f9"),
    legend.background = element_rect(fill = "#faf9f9"),
    axis.line = element_line(colour = "black", size = 0.25),
    panel.grid.major = element_line(colour = "grey95", size = 0.25),
    panel.grid.minor = element_line(colour = "grey95", size = 0.125),
    panel.border = element_rect(
      fill = NA,
      colour = "grey95",
      size = 0.25
    )
  ) +
  scale_x_continuous(
    labels = function(x)
      paste0(x, "%")
  )