拓端tecdat|R语言代写推特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,)
# 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")
