Riesen Rtweets

Assignment:

Get Trump’s tweets (realDonaldTrump) using get_timeline(). (You won’t need to use search_tweets() for this assignment.)
Find which hashtags he uses most and make a table.
Make a table of the number of tweets each day, and find the overall average number of tweets per day.
Create a plotly graphic of the number of tweets per day.
Create a table and a plotly histogram of the hour of the day that Trump tweets.
Create a table and a plotly histogram of the week days that Trump tweets.
Create a plotly heatmap of the weekday and time of day that Trump tweets.
Annotate the analysis and publish to rpubs.com.

library(tidyverse)
library(DT)
library(plotly)               # This package does interactive graphs
library(rtweet)               # This package accesses Twitter data

token <- create_token(
  app = "BreannaRiesen",
  consumer_key = "w6ReyWBcTZ9okuiCcU0tkdh4M",
  consumer_secret = "OTg1Wj3DXXPNCV8dh4BP1S3o92KUxFK8eKeleqwSgixTsU75tf",
  access_token = "1231727014568022016-53dfGwerymTvmjqR3EGvNS4qc0sHEg",
  access_secret = "VhAvieVsyxiIBnLoR6FnQ5PuLS3C5SnYhNDa4EhzBZUbj")

get_timeline(realDonaldTrump)

about_trump %>% 
  select(hashtags) %>%                   # Focus on the hashtags
  unnest() %>%                           # Separate multiple hashtags
  mutate(hashtags = tolower(hashtags)) %>%      # make all hashtags lowercase
  count(hashtags, sort=TRUE) %>%                # count how often they appear
  datatable()                                   # create an interactive table

realDonaldTrump_tweets %>% 
  group_by(day = date(created_at)) %>%    # extract the date, group by it
  summarize(tweets_per_day = n())         # count the number of tweets each day

realDonaldTrump_tweets %>% 
  group_by(day = date(created_at)) %>%    # extract the date, group by it
  summarize(tweets_per_day = n())         # count the number of tweets each day summarize(mean(tweets_per_day)) %>%

realDonaldTrump_tweets %>%
  mutate(day = date(created_at)) %>% 
  plot_ly(x = ~day) %>%                                        
  add_histogram() %>% 
  layout(title = "Number of tweets from @realDonaldTrump")

realDonaldTrump_tweets %>% 
  mutate(time = hour(created_at)) %>% 
  count(time) %>% 
  datatable(options = (list(pageLength = 24)), rownames = F)

realDonaldTrump_tweets %>% 
  mutate(time = with_tz(created_at, "America/New_York")) %>%    # convert to Eastern time zone
  mutate(time = hour(time)) %>%                                 # extract the hour
  plot_ly(x = ~time) %>%                                        # create plotly graph
  add_histogram() %>%                                               # make 
  layout(title = "When Does @realDonaldTrump Tweet?", 
         xaxis = list(title = "Time of Day (0 = midnight)"),
         yaxis = list(title = "Number of Tweets"))

realDonaldTrump_tweets %>% 
  mutate(day = wday(created_at, label = T)) %>% 
  mutate(hour = hour(with_tz(created_at, "America/New_York"))) %>% 
  plot_ly(x = ~day, y = ~hour) %>% 
  add_histogram2d(nbinsx = 7, nbinsy = 24) %>% 
  layout(title = "When Does @realDonaldTrump Tweet?", 
         xaxis = list(title = "Day of the Week"),
         yaxis = list(title = "Time of Day (0 = midnight"))

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