APratt Rtweet

This is an R Markdown Notebook.

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
library(lubridate)

token <- create_token(
  app = "APratt Rtweet project",
  consumer_key = "Qg4MasRdxRvyJ9rL4wYMzY1RG",
  consumer_secret = "1QBoTBPpLAUer8c6jhYHgNd8W4GCN8UTcXJFrGBenB70GOYmXO",
  access_token = "18624251-pUH8Yw2qkNU1UJlYe7ZDVGy7x8O06f3L0jYKpSa1N",
  access_secret = "A6yQ64IrhYwKbF6vUKmyjVYSbawPVHtnsW9d9NTQUnQHR")

get_token()        # this shows the token. make sure key is the same as consumer_key above

<Token>
<oauth_endpoint>
 request:   https://api.twitter.com/oauth/request_token
 authorize: https://api.twitter.com/oauth/authenticate
 access:    https://api.twitter.com/oauth/access_token
<oauth_app> APratt Rtweet project
  key:    Qg4MasRdxRvyJ9rL4wYMzY1RG
  secret: <hidden>
<credentials> oauth_token, oauth_token_secret
---

trump_tweets <- get_timeline("realDonaldTrump", n = 10000)

First, let’s get some tweets.

trump_tweets %>% 
  select(hashtags) %>% 
  unnest() %>% 
  mutate(hashtags = tolower(hashtags)) %>% 
  count(hashtags, sort = TRUE) %>% 
  datatable()

Let’s learn some hashtags–“kag” means Keep America Great, “democratshateamerica” means…you know what? Let’s stop there.

trump_tweets %>% 
  group_by(day = date(created_at)) %>% 
  summarize(tweets_per_day = n())

Donald Trump tweets a lot. Grab some covfefe and let’s dive in.

trump_tweets %>% 
  group_by(day = date(created_at)) %>% 
  summarize(tweets_per_day = n()) %>% 
  summarize(mean(tweets_per_day))

Data pulled today (2/25/2020) puts the mean number of tweets today at 28/29 My teenage nephew tweets about three times a week. Twitter is all but dead as a social media platform.

trump_tweets %>% 
  mutate(day = date(created_at)) %>% 
  plot_ly(x = ~day, marker = list(color = viridis::viridis_pal(option = "B", direction = -1)(25))) %>% 
  add_histogram() %>% 
  layout(title = "How Many Times Does the President Tweet Every Day?",
         xaxis = list(title = "Day"),
         yaxis = list(title = "Number of Tweets"))

Look, I made them orange.

trump_tweets %>%
  mutate(time = with_tz(created_at, "America/New_York")) %>% 
  mutate(time = hour(time)) %>% 
  count(time) %>% 
  datatable(options = list(pagelength = 24), rownames = F)

Does…does he have HootSuite? Or does an intern tweet the things he mumbles in his sleep?

trump_tweets %>% 
  mutate(time = with_tz(created_at, "America/New_York")) %>% 
  mutate(time = hour(time)) %>% 
  plot_ly(x = ~time, marker = list(color = viridis::viridis_pal(option = "B", direction = -1)(50))) %>% 
  add_histogram() %>% 
  layout(title = "Time of Day the President Tweets for No Reason",
  xaxis = list(title = "Time of Day (0 = Midnight)"),
  yaxis = list(title = "Tweets"))

Mid-morning spike? And late afternoon and around 11 pm. Does he do other things? Do you think he has a throw away account and trolls people all day? Why am I so invested in this.

trump_tweets %>% 
  mutate(Day = wday(created_at, label = T)) %>% 
  count(Day) %>% 
  datatable(rownames = F)

Here’s a table showing the number of tweets per day of the week. Apparently, Sunday truly is the day of rest. Monday and Wednesday are very busy.

trump_tweets %>% 
  mutate(day = wday(created_at, label = T)) %>% 
  plot_ly(x = ~day, marker = list(color = viridis::viridis_pal(option = "B", direction = -1)(25))) %>% 
  add_histogram() %>% 
  layout(title = "Donald Trump Tweets by Day", 
         xaxis = list(title = "Day of the week"),
         yaxis = list(title = "Number of Tweets"))

This is a much prettier showcase of Wednesday’s rants.

trump_tweets %>% 
  mutate(day = wday(created_at, label = T)) %>% 
  mutate(hour = hour(with_tz(created_at, "America/New_York"))) %>%
  plot_ly(x = ~day, y = ~hour, colors = colorRamp(c("orange", "blue")), type = "heatmap") %>% 
  add_histogram2d(nbinsx = 7, nbinsy = 24) %>% 
  layout(title = "The President's Tweets by Hour and Day",
         xaxis = list(title = "Day of the week"),
         yaxis = list(title = "Time of day (0 = midnight)"))

Mid-day Wednesday is when he fires off the most tweets (relative to the other times and days). Middle of Saturday night is also very popular.

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