index.qmd

---
title: "Violence against female journalists"
subtitle: "Visualising survey results"
author: "James Goldie, 360info"
date: "2022-04-27"
code-fold: true
theme: style/article.scss
---

```{r}
library(tidyverse)
library(here)
library(glue)
library(themes360info)
```

Let's bring the numbers in from the PR2Media survey, broken down by platform. I'm going to lengthene the data for plotting:

```{r}
survey_stats <-
  read_csv(here("data", "survey-counts-by-medium.csv")) %>%
  rename_with(
    ~ str_replace(str_replace(.x, "_n$", "-n"), "_p$", "-p"),
    -c(medium, total_n))

# add a total row
totals <-
  summarise(survey_stats,
    medium = "All platforms",
    total_n = sum(total_n),
    across(ends_with("-n"), sum)) %>%
  mutate(across(
    ends_with("-n"),
    list("prop" = ~ .x / total_n))) %>%
  rename_with(~ str_replace(.x, "-n_prop$", "-p"))

# now lengthen
survey_stats %>% 
  bind_rows(totals) %>%
  pivot_longer(
    cols = -c(medium, total_n),
    names_to = c("measure", ".value"),
    names_sep = "-") %>%
  # actually, i also want the inverse probabilities (ie. the nos) so that we can
  # plot "solid bars"
  rename(Yes_n = n, Yes_p = p) %>%
  mutate(
    No_n = total_n - Yes_n,
    No_p = 1 - Yes_p) %>%
  pivot_longer(
    cols = -c(medium, total_n, measure),
    names_to = c("response", ".value"),
    names_sep = "_") %>%
  mutate(
    measure_long = recode(measure,
      "has_bodyshaming"         =
        "Have you ever received<br>**body shaming comments**<br>online?",
      "has_nonsex_comments"     =
        "Have you ever received<br>annoying/harassing<br>**non-sexualcomments?**",
      "has_sexual_comments"     =
        "Have you ever received<br>annoying/harassing **sexual<br>comments?**",
      "has_violent_threats"     =
        "Have you ever received<br>**threats of physical violence?**",
      "has_doxxing"             =
        "Have you had your<br>**personal information<br>exposed?**",
      "has_misinfo_slander"     =
        "Have you ever been a<br>victim of **misinformation<br>or slander?**",
      "has_ethn_race_religion"  =
        "Have you ever received<br>an insult based on your<br>**ethnicity/religion/race?**",
      "has_wiretapping_hacking" =
        "Have you ever experienced<br>**wiretapping, hacking, interception<br>or monitoring** of your communications?",
    )) ->
survey_long
```

For the most part, the numbers are pretty similar across platforms:

```{r}
survey_long %>%
{
  ggplot(.) +
    aes(y = p, x = medium, fill = response) +
    geom_col(position = "stack") +
    geom_text(
      aes(label =
        glue("{scales::percent(p, accuracy = 1)} of {scales::number(total_n)}")),
      data = filter(., response == "Yes"),
      hjust = "left", nudge_y = 0.05,
      family = "Body 360info", size = 3,
      colour = colours_360("darkgrey")) +
    facet_wrap(vars(measure_long)) +
    coord_flip() +
    scale_y_continuous(limits = c(0, 1), labels = scales::percent_format()) +
    scale_fill_manual(
      values =
        colours_360("lightblue", "lightgrey") %>%
        set_names("Yes", "No"),
      guide = NULL) +
    theme_360() +
    theme(
      panel.grid.major.y = element_blank(),
      panel.grid.minor.y = element_blank(),
      panel.grid.minor.x = element_blank(),
      strip.text = element_textbox(height = unit(50, "points"), hjust = 0)) +
    labs(
      x = NULL, y = NULL,
      title = toupper("Violence against female journalists"),
      caption = paste(
        "**CHART:** James Goldie, 360info",
        "**DATA:** PR2Media",
        sep = "<br>"
      )
    )
} %>%
save_360plot(here("out", "survey-responses-by-medium.png"))
knitr::include_url(here("out", "survey-responses-by-medium.png"))
```