Project Part 2

Interactive and static plots of media platform active users from 2005 to 2019.

1. Packages I will use to read in and plot the data.

library(tidyverse)
library(echarts4r)

2. Read the data in from part 1.

media_activity  <- read_csv(here::here("media_activity.csv"))

Interactive graph

• Start with the data

• Group_by media platforms so there will be a “river” for each platform

• Use mutate to round active users so only 2 digits will be displayed when you hover over it.

• Use mutate to change Year so it will be displayed as end of year instead of beginning of year

• Use e_charts to create an e_charts object with Year on the x axis

• Use e_river to build “rivers” that contain active users by media platforms. The depth of each river represents the amount of users for each platform.

• Use e_tooltip to add a tooltip that will display based on the axis values

• Use e_title to add a title, subtitle, and link to subtitle

• Use e_theme to change the theme to roma

media_activity   %>%
  group_by(media_platforms)  %>%
  mutate(active_users = round(active_users, 2),
         Year = paste(Year, "12", "31", sep="-"))  %>% 
  e_charts(x = Year)   %>% 
  e_river(serie = active_users, legend=FALSE)  %>% 
  e_tooltip(trigger = "axis")  %>% 
  e_title(text = "Monthly Active Users, by Media Platform",
          subtext = "(in billions of users). Source: Our World in Data",
          sublink = "https://ourworldindata.org/social-connections-and-loneliness#social-media-started-in-the-early-2000s",
          left = "center")  %>% 
  e_theme("roma")  

Static graph

• Start with the data

• Use ggplot to create a new ggplot object. Use aes to indicate that Year will be mapped to the x axis; active_users will be mapped to the y axis; media_platforms will be the fill variable

• geom_area will display active_users

• scale_fill_discrete_divergingx is a function in the colorspace package. It sets the color palette to roma and selects a maximum of 12 colors for the different media platforms

• theme_classic sets the theme

• theme(legend.position = “bottom”) puts the legend at the bottom of the plot

• labs sets the y axis label, fill = NULL indicates that the fill variable will not have the labelled media_platforms

media_activity   %>% 
  ggplot(aes(x = Year, y = active_users, 
             fill = media_platforms)) +
  geom_area() +
  colorspace::scale_fill_discrete_divergingx(palette = "roma", nmax =19) +
  theme_classic() +
  theme(legend.position = "bottom") +
  labs( y = "in billions of users",
       fill = NULL)

ggsave(filename = here::here("_posts/2022-05-09-project-part-2/preview.png"))

These plots show a steady increase as well as decrease in active users for different platforms since 2005. Active users for Facebook, Twitter, and Pinterest continued to increase going into 2019.