Twitter networks

library(tidyverse)
library(DT)
library(igraph)
library(rtweet)
library(visNetwork)
library(graphTweets)            # This package turns twitter data into edge & node data

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> RTweets for PSYC 541
  key:    9z2JeDsn0047F1W96VWxZCEVV
  secret: <hidden>
<credentials> oauth_token, oauth_token_secret
---

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

senate_tweets <- get_timeline(senate$screen_name, n = 200)

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# This creates the network with some commands from graphTweets
# The variables in the parentheses of gt_edges() are used, so in this case we're using retweets
senate_retweets_network <- senate_tweets %>% 
  filter(retweet_screen_name %in% senate$screen_name) %>%     # <- This is a new line and important.
  gt_edges(screen_name, retweet_screen_name, text) %>%             # It only keep retweets of other cabinet members
  gt_graph()


# This next line gets the nodes
senate_retweets_nodes <- as_data_frame(senate_retweets_network, what = "vertices")

# This adds some additional info to the nodes, so we get the names on hover
# and the size of the node is based on its degree, etc.
senate_retweets_nodes <- senate_retweets_nodes %>% 
  mutate(id = name) %>% 
  mutate(label = name) %>% 
  mutate(title = name) %>% 
  mutate(degree = degree(senate_retweets_network)) %>% 
  mutate(value = degree)

# This gets the edges, similar to how we got the nodes above
senate_retweets_edges <- as_data_frame(senate_retweets_network, what = "edges")

# This puts the text of the tweet itself into the edge
# so when you hover over a line in the diagram it will show the tweet
senate_retweets_edges <- senate_retweets_edges %>% 
  mutate(title = text)

# Creates the diagram
visNetwork(senate_retweets_nodes, senate_retweets_edges, main = "US senate officials retweet network") %>% 
  visIgraphLayout(layout = "layout_nicely") %>% 
  visEdges(arrows = "to")

senate_retweet_network %>% 
  vcount()

senate_retweet_network %>%
  ecount()

senate_retweet_network %>%
  edge_density()

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

senate_retweets_nodes <- senate_retweets_nodes %>% 
  mutate(group = membership(infomap.community(senate_retweets_network)))

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

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