R Notebook

library(tidyverse)
library(ggplot2)
library(DT)
library(igraph)
library(rtweet)
library(visNetwork)
library(graphTweets)  
library(dplyr)

token <- create_token(
  app = "US-Senator",
  consumer_key = "D38ITwMk7n9uMGjlPCz3XWTHV",
                  consumer_secret = "EK2O62bab0W4fJ9Gj97uiEfE4Eeygj0iA6E50vsg40U1BZp6JT",
                  access_token = "1226982887783690241-3qqlXFAtNZq2KXBu0nIp1XXwKcclvo" ,
                  access_secret = "8eLnNPnMfYU0pacVldSv0xjUtiyIQVqatuw1f0GJQ2jSh")

Saving auth to '/cloud/home/r454505/.config/R/rtweet/create_token.rds'

get_token()        

<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> rtweet
  key:    D38ITwMk7n9uMGjlPCz3XWTHV
  secret: <hidden>
<credentials> oauth_token, oauth_token_secret
---

USsenate_tweets <- get_timeline("US senators", n = 200)

This collects a list of US Senators and thier last 200 tweets.

USsenate_retweet_network <- USSenate_tweets %>% 
  gt_edges(screen_name, retweet_screen_name, text) %>% 
  gt_graph()


USsenate_retweet_nodes <- as_data_frame(USsenate_retweet_network, what = "vertices")


USsenate_retweet_nodes <- USsenate_retweet_nodes %>% 
  mutate(id = name) %>% 
  mutate(label = name) %>% 
  mutate(title = name) %>% 
  mutate(degree = degree(USsenate_retweet_network)) %>% 
  mutate(value = degree)


USsenate_retweet_edges <- as_data_frame(USsenate_retweet_network, what = "edges")


USsenate_retweet_edges <- USsenate_retweet_edges %>% 
  mutate(title = text)


visNetwork(USsenate_retweet_nodes, USsenate_retweet_edges, main = "US Senate officials retweet network") %>% 
  visIgraphLayout(layout = "layout_nicely") %>% 
  visEdges(arrows = "to")

Retweet network of US Senate

USsenate_retweet_network %>% 
  vcount()

[1] 854

USsenate_retweet_network %>% 
  ecount()

[1] 817

USsenate_retweet_network %>%
  edge_density()

[1] 0.001121541

USsenate_retweet_nodes %>%
  select(name, degree) %>%
  datatable()

USsenate <- lists_members(slug = "us-senate", owner_user = "TwitterGov")

USsenate_tweets <- get_timeline(USsenate$screen_name, n = 180)

USsenate_retweets_network <- USSenate_tweets %>% 
  filter(retweet_screen_name %in% USSenate_tweets$screen_name) %>% 
  gt_edges(screen_name, retweet_screen_name, text) %>%
  gt_graph()

USsenate_retweets_nodes <- as_data_frame(USsenate_retweets_network, what = "vertices")


USsenate_retweets_nodes <- USsenate_retweets_nodes %>% 
  mutate(id = name) %>% 
  mutate(label = name) %>% 
  mutate(title = name) %>% 
  mutate(degree = degree(USsenate_retweets_network)) %>% 
  mutate(value = degree)


USsenate_retweets_edges <- as_data_frame(USsenate_retweets_network, what = "edges")


USsenate_retweets_edges <- USsenate_retweets_edges %>% 
  mutate(title = text)


visNetwork(USsenate_retweets_nodes, USsenate_retweets_edges, main = "US Senate officials retweet network") %>% 
  visIgraphLayout(layout = "layout_nicely") %>% 
  visEdges(arrows = "to")

This is a network diagram of US Senate officials retweets with communities. This includes the option to select by group and each group is represented by diffferent colors.

USsenate_retweets_nodes <- USsenate_retweets_nodes %>% 
  mutate(group = membership(infomap.community(USsenate_retweets_network)))

visNetwork(USsenate_retweets_nodes, USsenate_retweets_edges, main = "US Senate officials retweet network") %>% 
  visIgraphLayout(layout = "layout_nicely") %>% 
  visEdges(arrows = "to") %>%   
  visOptions(highlightNearest = T, nodesIdSelection = T, selectedBy = "group")

This is a network diagram of US Senate officials retweets with communities. This includes the option to select by group and each group is represented by diffferent colors.