Wikipedia Page Views

1. This code will gather all of the pageview data for the Gun control Wikipedia article over the course of five years. It also renames the data to gun_control for convenience.

gun_control <- article_pageviews(article = "Gun control", start = as.Date("2015-1-1"), end = as.Date("2020-12-31"))

This code will graph the gun_control data gathered from the previous code.

gun_control %>%
  ggplot(aes(x = date, y = views)) +
  geom_line()

2. This code will show the top twenty days for pageviews on the Gun control article.

gun_control%>%
  select(article, views, date) %>%
  arrange(-views) %>%
  top_n(20, views)

NA

3. This code gathers the data for the top pages searched on Wikipedia the day after the Las Vegas shooting on 10-01-2017.

top <- top_articles(start = as.Date("2017-10-2"))

This code ranks the most to least viewed Wikipedia pages the day after the shooting. It also filters that data so that the “Main Page” and “Special: Search” pages aren’t counted.It formats the data into an easy to navigate data table.

top %>% 
  select(article, views) %>%
  filter(!article == "Main_Page", !article == "Special:Search") %>% 
  datatable(class = 'cell-border stripe') %>% 
  formatStyle("article", backgroundColor = "lavenderblush")

NA

This code gathers the data for the top pages searched on Wikipedia the day after the Florida school shooting on 02-14-2018.

top <- top_articles(start = as.Date("2018-2-15"))

Like with the code for the Las Vegas data, this ranks the most to least viewed Wikipedia pages the day after the shooting, filters out the “Main Page” and “Special: Search” pages, and organizes the data into a data table.

top %>% 
  select(article, views) %>%
  filter(!article == "Main_Page", !article == "Special:Search") %>% 
  datatable(class = 'cell-border stripe') %>% 
  formatStyle("article", backgroundColor = "lavenderblush")

NA

4. This code shows a graph of the pageviews of the Gun control Wikipedia page one week before and two weeks after the Las Vegas shooting so you can see the amount of traffic to that page after the shooting.

vegas <- article_pageviews(article = "Gun_control",
                           start = as.Date("2017-09-24"),
                           end = as.Date("2017-10-15"))

vegas <- vegas %>%
  mutate(day = -7:14) %>%
  mutate(event = "Vegas")

vegas %>%
  ggplot(aes(x = day, y = views)) +
  geom_line()

This code does the same as the one before but for the Florida school shooting.

florida <- article_pageviews(article = "Gun_control",
                             start = as.Date("2018-2-7"),
                             end = as.Date("2018-2-28"))
florida <- florida %>%
  mutate(day= -7:14) %>%
  mutate(event = "Florida")

florida %>%
  ggplot(aes(x = day, y = views)) +
  geom_line()

This code combines the individual graph data from the Las Vegas and Florida graphs into one.

shootings <- bind_rows(vegas, florida)

shootings %>% 
  ggplot(aes(x = day, y = views, color = event)) +
  geom_line() +
  theme_minimal() +
  labs(x = "Days Before and After Shooting", 
       y = "Page Views", 
       color = "Shooting", 
       title = "Views of the Wikipedia Gun Control Article before and after Two Mass Shootings")