2015-03-04 11:36:31 +01:00
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require(lubridate)
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require(XML)
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require(stringr)
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require(foreach)
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require(doParallel)
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source("issuecomp-functions.R")
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2015-03-04 11:56:20 +01:00
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setwd("E:/max.mehl")
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2015-03-04 11:36:31 +01:00
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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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# Import issues and prepare everything
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# Will only be filled after the large categorisation loop
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issues <- data.frame(date = drange)
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issuelist <- readLines("issues-v2.xml")
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issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
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issuelist <- xmlToList(issuelist)
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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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# MATCH TWEETS ------------------------------------------------------------
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# Create folder where all results will be saved (saver for backup and import)
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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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# Tag expansion for plural, genetiv etc
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tagexpand <- c("", "s", "n", "en", "er", "e")
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# Parameters for parallelisation
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writeLines(c(""), "issuecomp-analysis.log")
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cl<-makeCluster(7)
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registerDoParallel(cl)
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# START CAT LOOP
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foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
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# Go through every day
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curdate <- issues$date[d]
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cat(paste(as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
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# Put all tweets from specific day in a temporary DF
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tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
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for(t in 1:nrow(tweets_curday)){
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# cat(paste("Starting tweet", t, "of",as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
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# Select tweet's text, make it lowercase and remove hashtag indicators (#)
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curtext <- as.character(tweets_curday$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(issueheads)) {
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curissue <- issueheads[i]
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curtags <- as.character(issuelist[[curissue]])
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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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curacro <- checkAcronym(string = curtag)
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# Check if tag is some kind of specific hashtag. If so, do not handle as acronym, but don't expand it either
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if(str_detect(curtag, "^#")) {
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curacro <- FALSE # hashtags like #WM2014 are also written as #wm2014, so we need case-insensitivity
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curhash <- TRUE # But we need to mark it as hashtag, so it doesn't get extended or Levenshtein distance > 0
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curtag <- str_replace(curtag, "#", "")
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curchars <- curchars - 1
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} else {
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curhash <- FALSE
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}
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# Now expand the current tag by possible suffixes that may be plural forms
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# Only do if it isn't an acronym or specific hastag
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if(!curacro && !curhash) {
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for(e in 1:length(tagexpand)) {
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curtag[e] <- str_c(curtag[1], tagexpand[e])
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}
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}
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# Set Levenshtein distance depending on char length, acronym and hashtag status
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if(curchars <= 6 || curacro || curhash) { # Distance = 1 if 7 chars or longer
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curdistance <- 0
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} else {
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curdistance <- 1
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}
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# Match current tweet with tag.
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2015-03-04 11:56:20 +01:00
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# Allow 1 Levenshtein distance if tag is >= 5 letters and no hashtag or acronym
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# Make is case-sensitiv if tag is an acronym
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2015-03-04 11:36:31 +01:00
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tags_found <- NULL
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# Match the tweet with each variation of tagexpand
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for(e in 1:length(curtag)) {
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tags_found[e] <- smartPatternMatch(curtext, curtag[e], curdistance, curacro)
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}
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tags_found <- any(tags_found)
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curtag <- curtag[1]
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if(tags_found == TRUE) {
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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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#
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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,"\";",curissue,";",curtag), curfile, append = TRUE)
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# cat(paste("Match!\n"), file="issuecomp-analysis.log", append=TRUE)
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# data.frame(date=curdate, issue=curissue)
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break # next issue, no more tags from same issue
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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,i,id_folder,oldissue,oldtag,s,t,tags_found)
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stopCluster(cl)
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