R语言推特twitter转发可视化分析

包含术语“生物信息学”的推文示例

第1步: 加载所需的软件包

# load packages

library(twitteR)

library(igraph)

library(stringr)

第2步: 收集关于“生物信息学”的推文

# tweets in english containing "bioinformatics"

dm_tweets = searchTwitter("bioinformatics", n=500, lang="en") 

# get text

dm_txt = sapply(dm_tweets, function(x) x$getText())

第3步:识别转发

# regular expressions to find retweets

grep("(RT|via)((?:\\b\\W*@\\w+)+)", dm_tweets, 

ignore.case=TRUE, value=TRUE)

# which tweets are retweets

rt_patterns = grep("(RT|via)((?:\\b\\W*@\\w+)+)", 

dm_txt, ignore.case=TRUE)

# show retweets (these are the ones we want to focus on)

dm_txt[rt_patterns] 

第4步:收集谁转发和谁发布

我们将使用这些结果来形成边缘列表以创建图形

# create list to store user names

who_retweet = as.list(1:length(rt_patterns))

who_post = as.list(1:length(rt_patterns))

# for loop

for (i in 1:length(rt_patterns))

   # get tweet with retweet entity

   twit = dm_tweets[[rt_patterns[i]]]

   # get retweet source 

   poster = str_extract_all(twit$getText(),

      "(RT|via)((?:\\b\\W*@\\w+)+)") 

   #remove ':'

   poster = gsub(":", "", unlist(poster)) 

   # name of retweeted user

   who_post[[i]] = gsub("(RT @|via @)", "", poster, ignore.case=TRUE) 

   # name of retweeting user 

   who_retweet[[i]] = rep(twit$getScreenName(), length(poster)) 

}

# unlist

who_post = unlist(who_post)

who_retweet = unlist(who_retweet)

第5步: 从编辑清单创建图形

# two column matrix of edges

retweeter_poster = cbind(who_retweet, who_post)

# generate graph

rt_graph = graph.edgelist(retweeter_poster)

# get vertex names

ver_labs = get.vertex.attribute(rt_graph, "name", index=V(rt_graph))

第6步: 让我们绘制图

# choose some layout

glay = layout.fruchterman.reingold(rt_graph)

# plot

par(bg="gray15", mar=c(1,1,1,1))

plot(rt_graph, layout=glay,

   vertex.color="gray25",

   vertex.size=10,

   vertex.label=ver_labs,

   vertex.label.family="sans",

   vertex.shape="none",

   vertex.label.color=hsv(h=0, s=0, v=.95, alpha=0.5),

   vertex.label.cex=0.85,

   edge.arrow.size=0.8,

   edge.arrow.width=0.5,

   edge.width=3,

   edge.color=hsv(h=.95, s=1, v=.7, alpha=0.5))

# add title

title("\nTweets with 'bioinformatics':  Who retweets whom",

   cex.main=1, col.main="gray95") 


第7步:让我们试着给它一个更生物信息学的外观

# another plot

par(bg="gray15", mar=c(1,1,1,1))

plot(rt_graph, layout=glay,

   vertex.color=hsv(h=.35, s=1, v=.7, alpha=0.1),

   vertex.frame.color=hsv(h=.35, s=1, v=.7, alpha=0.1),

   vertex.size=5,

   vertex.label=ver_labs,

   vertex.label.family="mono",

   vertex.label.color=hsv(h=0, s=0, v=.95, alpha=0.5),

   vertex.label.cex=0.85,

   edge.arrow.size=0.8,

   edge.arrow.width=0.5,

   edge.width=3,

   edge.color=hsv(h=.35, s=1, v=.7, alpha=0.4))

# add title

title("\nTweets with 'bioinformatics':  Who retweets whom",

   cex.main=1, col.main="gray95", family="mono")


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转载自blog.csdn.net/qq_19600291/article/details/79961928