Load packages:

library(tidyverse)

## ── Attaching packages ──────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──

## ✔ ggplot2 3.1.0     ✔ purrr   0.3.0
## ✔ tibble  2.0.1     ✔ dplyr   0.7.8
## ✔ tidyr   0.8.2     ✔ stringr 1.3.1
## ✔ readr   1.3.1     ✔ forcats 0.3.0

## ── Conflicts ─────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()

library(DT)
library(plotly)               # This package does interactive graphs

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

library(rtweet)               # This package accesses Twitter data

## 
## Attaching package: 'rtweet'

## The following object is masked from 'package:purrr':
## 
##     flatten

library(lubridate)  

## 
## Attaching package: 'lubridate'

## The following object is masked from 'package:base':
## 
##     date

Get 10000 of Trump’s tweets:

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

Which hastage does Trump use?

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

A table of the number of tweets each day

trump_tweets %>% 
  group_by(Day = date(created_at)) %>% 
  summarise(tweets_per_day = n()) %>% 
  datatable()

The overall average number of tweets per day

trump_tweets %>% 
  group_by(Day = date(created_at)) %>% 
  summarise(tweets_per_day = n()) %>% 
  summarise(mean(tweets_per_day))

The number of tweets per day

trump_tweets %>% 
  group_by(Day = date(created_at)) %>% 
  plot_ly(x = ~Day) %>% 
  add_histogram()

A table of the hour of the day that Trump tweets

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

A histogram of the hour of the day that Trump tweets

trump_tweets %>% 
  mutate(Time = hour(with_tz(created_at, "America/New_York"))) %>% 
  plot_ly(x = ~Time) %>% 
  add_histogram() %>%
  layout(title = "When Trump Tweets",
         xaxis = list(title = "Time of Day (0 = midnight)"), 
         yaxis = list(title = "Number of Tweets"))

A table of the week days that Trump tweets

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

A histogram of the week days that Trump tweets

trump_tweets %>% 
  mutate(Day = wday(created_at, label = T)) %>% 
  plot_ly(x = ~Day) %>% 
  add_histogram() %>%
  layout(title = "When Trump Tweets",
         xaxis = list(title = "Day of the week"), 
         yaxis = list(title = "Number of Tweets"))

A plotly heatmap of the weekday and time of day that Trump tweets

trump_tweets %>% 
  mutate(Time = hour(with_tz(created_at, "America/New_York"))) %>% 
  mutate(Day = wday(created_at, label = T)) %>% 
  plot_ly(x = ~Day, y = ~Time) %>% 
  add_histogram2d() %>% 
  layout(title = "When Trump Tweets", 
         xaxis = list(title = "Day of the week"),
         yaxis = list(title = "Time of Day (0 = midnight)"))

trump_tweets %>% 
  mutate(Time = hour(with_tz(created_at, "America/New_York"))) %>% 
  mutate(Day = wday(created_at, label = T)) %>% 
  plot_ly(x = ~Day, y = ~Time) %>% 
  add_histogram2dcontour() %>% 
  layout(title = "When Trump Tweets", 
         xaxis = list(title = "Day of the week"),
         yaxis = list(title = "Time of Day (0 = midnight)"))