downloads user timeline and plots before and after interactions from a cutoff date and time

before_and_after_interactions.R

# load packages

library("twitteR")
library("dplyr")
library("lubridate")

api_key <- "your key"

api_secret <- "your secret"

access_token <- "your token"

access_token_secret <- "your token secret"

setup_twitter_oauth(api_key, api_secret, access_token, access_token_secret)

# for @TurfDiseases account
 tweets <- userTimeline("TurfDiseases", n = 1000, includeRts = TRUE)
 tweetsDF <- twListToDF(tweets)
 original <- filter(tweetsDF, isRetweet == FALSE)
 
 # cutoff tweets from specified date and time
 cutoff <- ymd_hms("2015-01-16 12:00:00")
 
 original$created <- ymd_hms(original$created)
 
 new <- filter(original, created > cutoff)
 
 old <- filter(original, created < cutoff)

 new$interaction <- new$favoriteCount + new$retweetCount
 old$interaction <- old$favoriteCount + old$retweetCount
 
mean(old$interaction)
mean(new$interaction)
median(old$interaction)
median(new$interaction)
 
plot(density(old$interaction), col = "blue",
     xlab = "interaction per tweet (favorite + retweet)",
     main = "@TurfDiseases tweets before & after 2015-01-16 12:00")
lines(density(new$interaction), col = "red")
 text(x = 5, y = .4, adj = 0,
      labels = "before 2015-01-16 12:00\nn = 699\nmean = 1.49\nmedian = 0",
      col = "blue")
 text(x = 10, y = .2, adj = 0,
      labels = "after 2015-01-16 12:00\nn = 39\nmean = 2.62\nmedian = 2",
      col = "red")