119 lines
3.8 KiB
R
119 lines
3.8 KiB
R
require(lubridate)
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require(XML)
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require(ggplot2)
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require(reshape2)
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require(stringr)
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source("issuecomp-functions.R")
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load(file = "tweets_untagged.RData")
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# Create date range
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date_start <- as.Date("2014-01-01")
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date_end <- as.Date("2014-12-31")
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drange <- as.integer(date_end - date_start)
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drange <- date_start + days(0:drange)
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# MATCH TWEETS ------------------------------------------------------------
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id_folder <- "matched-ids"
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unlink(id_folder, recursive = TRUE)
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dir.create(id_folder)
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issues <- data.frame(date = drange)
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issuelist <- xmlToList("issues.xml")
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issueheads <- names(issuelist)
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issues[issueheads] <- 0
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tweets$issue <- ""
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tweets$tags <- ""
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for(d in 1:nrow(issues)) {
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# Go through every day
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curdate <- issues$date[d]
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cat(as.character(curdate),"\n")
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# Put all tweets from specific day in a temporary DF
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tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
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for(t in 1:nrow(tweets_curday)){
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# Select tweet's text, make it lowercase and remove hashtag indicators (#)
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curtext <- as.character(tweets_curday$text[t])
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curtext <- str_replace_all(curtext, "#", "")
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curid <- as.character(tweets_curday$id_str[t])
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# Now test each single issue (not tag!)
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for(i in 1:length(issuelist)) {
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curtags <- as.character(issuelist[[i]])
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curissue <- names(issuelist)[i]
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curfile <- str_c(id_folder,"/",curissue,".csv")
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# Now test all tags of a single issue
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for(s in 1:length(curtags)) {
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curtag <- curtags[s]
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curchars <- nchar(curtag, type = "chars")
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# Check if tag is an acronym. If so, ignore.case will be deactivated in smartPatternMatch
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if(curchars <= 4) {
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curacro <- checkAcronym(string = curtag, chars = curchars)
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} else {
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curacro <- FALSE
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}
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# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow 2 (Levenshtein distance)
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tags_found <- smartPatternMatch(curtext, curtag, curchars, curacro)
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if(tags_found == 1) {
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# Raise number of findings on this day for this issue by 1
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issues[d,curissue] <- issues[d,curissue] + 1
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# Add issue and first matched tag of tweet to tweets-DF
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oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
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tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
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oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
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tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
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# Add information to file for function viewPatternMatching
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write(str_c(curdate,";\"",curid,"\";",curtag), curfile, append = TRUE)
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break
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}
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else {
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#cat("Nothing found\n")
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}
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} # /for curtags
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} # /for issuelist
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} # /for tweets_curday
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} # /for drange
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rm(tweets_curday,curacro, curchars, curdate,curfile,curid,curissue,curtag,curtags,curtext,d,date_end,date_start,drange,i,id_folder,oldissue,oldtag,s,t,tags_found)
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# SAVING ------------------------------------------------------------------
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row.names(tweets) <- NULL
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write.csv(tweets, "tweets.csv")
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save(tweets, file="tweets.RData")
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# VISUALS -----------------------------------------------------------------
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# Level: days
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issues_melt <- melt(issues,id="date")
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ggplot(issues_melt,aes(x=date,y=value,colour=variable,group=variable)) + geom_line(size=1)
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ggplot(issues_melt,aes(x=date,y=value,colour=variable,group=variable)) + geom_smooth(size=1,method="loess",formula = y ~ x, se=FALSE)
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# POSSIBLY USEFUL CODE ----------------------------------------------------
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# Limits of list
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length(issuelist)
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length(issuelist[[2]])
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# Select all tweets from current day in drange
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tweets_curday <- tweets[tweets[, "created_at"] == drange[5], ]
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# Is column a issue counting column?
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str_detect(names(issues[2]), "^issue") |