ANT 291

Social Network Analysis and Social Media

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    • Instructor: Fuji Lozada
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25 Sep 2017

25 Sep

http://www.interhacktives.com/2017/01/25/scrape-tweets-r-journalists/

rm(list=ls())

library(igraph)
data <- as.matrix(read.csv(“tweet-incid.csv”,row.names=1))

tweet.net <- data %*% t(data)
topic.net <- t(data) %*% data

diag(tweet.net) <- NA
diag(topic.net) <- NA

tweet.g <- graph.adjacency(tweet.net,mode=”undirected”,
weighted=NULL, diag=FALSE)

topic.g <- graph.adjacency(topic.net, weighted=TRUE,
mode=”undirected”, diag=FALSE)

e.wt <- get.edge.attribute(topic.g, “weight”)

la <- layout.fruchterman.reingold(tweet.g)
plot(tweet.g, layout=la, vertex.size=15,edge.width=1)

la <- layout.fruchterman.reingold(topic.g)
plot(topic.g, layout=la, vertex.size=15,edge.width=e.wt)

topic.degree <- degree(topic.g)
plot(topic.g, layout=la, vertex.size=5*topic.degree, edge.width=e.wt)

topic.between <- betweenness(topic.g)
View(topic.between)

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