R中的子图文本分析（igraph）

Question

I am curious how to access additional attributes for a graph which are associated with the edges. To follow along here is a minimal example:

library("igraph")
library("SocialMediaLab")

myapikey =''
myapisecret =''
myaccesstoken = ''
myaccesstokensecret = ''

tweets <- Authenticate("twitter",
                       apiKey = myapikey,
                       apiSecret = myapisecret,
                       accessToken = myaccesstoken,
                       accessTokenSecret = myaccesstokensecret) %>%
Collect(searchTerm="#trump", numTweets = 100,writeToFile=FALSE,verbose=TRUE)
g_twitter_actor <- tweets %>% Create("Actor", writeToFile=FALSE)
c <- igraph::components(g_twitter_actor, mode = 'weak')
subCluster <- induced.subgraph(g_twitter_actor, V(g_twitter_actor)[which(c$membership == which.max(c$csize))])

The initial tweets contains the following columns

colnames(tweets)
 [1] "text"            "favorited"       "favoriteCount"   "replyToSN"       "created_at"      "truncated"       "replyToSID"      "id"             
 [9] "replyToUID"      "statusSource"    "screen_name"     "retweetCount"    "isRetweet"       "retweeted"       "longitude"       "latitude"       
[17] "from_user"       "reply_to"        "users_mentioned" "retweet_from"    "hashtags_used"

How can I access the text property for the subgraph in order to perform text analysis? E(subCluster)$text does not work

Answer 1

E(subCluster)$text does not work because the values for tweets$text are not added to the graph when it is made. So you have to do that manually. It's a bit of a pain, but doable. Requires some subsetting of the tweets data frame and matching based on user names.

First, notice that the edge types are in a particular order: retweets, mentions, replies. The same text from a particular user can apply to all three of these. So I think it makes sense to add text serially.

> unique(E(g_twitter_actor)$edgeType)
[1] "Retweet" "Mention" "Reply"  

Using dplry and reshape2 makes this easier.

library(reshape2); library(dplyr)
#Make data frame for retweets, mentions, replies
rts <- tweets %>% filter(!is.na(retweet_from))
ms <- tweets %>% filter(users_mentioned!="character(0)")
rpls <- tweets %>% filter(!is.na(reply_to))

Since users_mentioned can contain a list of individuals, we have to unlist it. But we want to associate the users mentioned with the user who mentioned them.

#Name each element in the users_mentioned list after the user who mentioned
names(ms$users_mentioned) <- ms$screen_name
ms <- melt(ms$users_mentioned) #melting creates a data frame for each user and the users they mention

#Add the text
ms$text <- tweets[match(ms$L1,tweets$screen_name),1]

Now add each of these to the network as an edge attribute by matching the edge type.

E(g_twitter_actor)$text[E(g_twitter_actor)$edgeType %in% "Retweet"] <- rts$text
E(g_twitter_actor)$text[E(g_twitter_actor)$edgeType %in% "Mention"] <- ms$text
E(g_twitter_actor)$text[E(g_twitter_actor)$edgeType %in% "Reply"] <- rpls$text

Now you can subset and get the edge value for text.

subCluster <- induced.subgraph(g_twitter_actor, 
                           V(g_twitter_actor)[which(c$membership == which.max(c$csize))])