R Notebook

1. Create a graph of views of the Gun control article on wikipedia over a several year period, like we did for Influenza.

This graph shows the views of the article “Gun control” over a period of a couple years.

guns %>% 
  ggplot(aes(x = date, y = views)) +
  geom_line(color= "red") +
  labs(x = "Date", y = "Wikipedia Views", title = "Views of Wikipedia's Gun control Article")

The views of “Gun control” peaked just after 2018.

2. Create a table showing the highest days for viewing the Gun control article.

This table is showing the number of views that the article had on a certain date.

guns %>%
  arrange(views)

Feburary 19, 2018 had the highest amount of views.

3. Look at top_articles the next day after the Vegas and Florida shootings to see if people are searching for information about those events. Create two tables using datatable() of the top articles for those two days.

This is the day after the Vegas shooting.

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

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

NA

The Las Veags shooting was the 4th most popular search.

This is the day after the Florida shooting.

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

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

NA

The Florida shooting was not yet on a Wiki page, but other school shooting were a popular search.

4. Compare Wikipedia views of the Gun control article 1 week before and 2 weeks after the Vegas & Florida shootings with a ggplot.

vegas <- article_pageviews(article = "Gun_control",
                           start = as.Date("2017-9-25"),
                           end = as.Date("2017-10-16"))

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

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")

vegas <- article_pageviews(article = "Gun_control",
                           start = as.Date("2017-9-25"),
                           end = as.Date("2017-10-16"))
vegas <- vegas %>% 
  mutate(day = -7:14) %>% 
  mutate(event = "Vegas")

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")

shootings <- bind_rows(vegas, florida)

shootings %>% 
  ggplot(aes(x = day, y = views, color = event)) +
  geom_line() +
  theme_minimal() +
  labs(x = "7 Days before/14 after Shooting", 
       y = "Wikipedia Views", 
       color = "Event", 
       title = "Views of the Wikipedia Gun Control Article before and after Two Mass Shootings")

This graph shows the combination of both shootings and the spike of views on the shootings the day of and the weeks after they occurred.