country small multiples

packages:

library(tidyverse)

## ── Attaching packages ───────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──

## ✔ ggplot2 3.1.0       ✔ purrr   0.2.5  
## ✔ tibble  2.1.1       ✔ dplyr   0.8.0.1
## ✔ tidyr   0.8.2       ✔ stringr 1.3.1  
## ✔ readr   1.1.1       ✔ forcats 0.3.0

## ── Conflicts ──────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()

#install.packages("gghighlight")
library(ggplot2)
library(gghighlight)

set up data:

country_trust <- read_csv("data/clean_country-fake-news-concern.csv")

## Parsed with column specification:
## cols(
##   country = col_character(),
##   `Not at all concerned` = col_double(),
##   `Not very concerned` = col_double(),
##   `Somewhat concerned` = col_double(),
##   `Very concerned` = col_double(),
##   `Extremely concerned` = col_double(),
##   Concerned = col_double(),
##   `Not concerned` = col_double(),
##   Mean = col_double()
## )

country_trust_stack <- country_trust %>% select(country, `Somewhat concerned`, Concerned, `Not concerned`) %>% gather(concern, percent, `Somewhat concerned`, Concerned, `Not concerned`)

country_trust_stack <- country_trust_stack %>% mutate(percent_new = percent * 100)

just_US <- country_trust_stack %>% filter(country == "US")

Small multiples to look at: Q_FAKE_NEWS_2_6. To what extent, if at all, are you concerned about the following: - The use of the term fake news (e.g. by politicians, others) to discredit news media they don’t like

create a theme to highlight

my_theme <- function(){
  list(
      theme_minimal(),
      scale_fill_manual(values=c("tomato", "#41b6c4", "#999999"), 
                       name="Level of Concern",
                       breaks=c("Concerned", "Somewhat concerned", "Not concerned"),
                       labels=c("Concerned", "Somewhat concerned", "Not concerned")) 
    )
}

test plot with USA:

US_trust <- ggplot(just_US, aes(reorder(concern, percent_new), percent_new, width=.5)) +
  geom_bar(aes(fill = concern), stat = "identity") + 
  my_theme() +
  coord_flip() +
  labs(title = "Level of concern over the term fake news in each country surveyed", x = "level of concern", y = "percent", caption = "Source: Reuters 2018 Digital News Report") +
  geom_text(aes(label = percent_new), colour = "white", hjust = 1.3)

US_trust #+ gghighlight(percent_new == 50)

small multiples:

all_countries <- ggplot(country_trust_stack, aes(reorder(concern, percent_new), percent_new, width=.6)) +
  geom_bar(stat = "identity", aes(fill = concern)) +
  my_theme() +
  coord_flip() +
  labs(title = "Level of concern over the term fake news in each country surveyed", x = "level of concern", y = "percent", caption = "Source: Reuters 2018 Digital News Report") +
  facet_wrap(~ country) + 
  theme_minimal()

all_countries

export:

# PDF or PNG 
# to speficiy a chart add a "plot = plot_name" parameter after the file name.
ggsave("US_only.pdf", plot = US_trust, width = 8, height = 8, units = "in", dpi = 320)
ggsave("US_only.png", plot = US_trust, width = 8, height = 8, units = "in", dpi = 320)

ggsave("all_countries.pdf", plot = all_countries, width = 11, height = 8, units = "in", dpi = 320)
ggsave("all_countries.png", plot = all_countries, width = 11, height = 8, units = "in", dpi = 320)