ongoing categorisation
This commit is contained in:
@@ -1,340 +1,3 @@
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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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# Now expand the current tag by possible suffixes that may be plural forms
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if(!curacro) {
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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
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if(curchars <= 4) {
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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. If >= 5 letters allow 1 changed letter, if >=8 letters allow also 1 (Levenshtein distance)
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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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# 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 <- readLines("issues.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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tagexpand <- c("", "s", "n", "en", "er", "e")
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# Parallelisation
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writeLines(c(""), "issuecomp-analysis.log")
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cl<-makeCluster(4)
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registerDoParallel(cl)
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df<-foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
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#for(d in 1:nrow(issues)) {
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# Go through every day
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curdate <- issues$date[d]
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cat(paste(as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
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# Put all tweets from specific day in a temporary DF
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tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
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for(t in 1:nrow(tweets_curday)){
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cat(paste("Starting tweet", t, "of",as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
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# Select tweet's text, make it lowercase and remove hashtag indicators (#)
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curtext <- as.character(tweets_curday$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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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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# Now expand the current tag by possible suffixes that may be plural forms
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if(!curacro) {
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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
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if(curchars <= 4) {
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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. If >= 5 letters allow 1 changed letter, if >=8 letters allow also 1 (Levenshtein distance)
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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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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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library(foreach)
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library(doParallel)
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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 <- readLines("issues.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$tags <- ""
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tagexpand <- c("", "s", "n", "en", "er", "e")
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# Parallelisation
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writeLines(c(""), "issuecomp-analysis.log")
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cl<-makeCluster(4)
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registerDoParallel(cl)
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df<-foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
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#for(d in 1:nrow(issues)) {
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# Go through every day
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curdate <- issues$date[d]
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cat(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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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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# Now expand the current tag by possible suffixes that may be plural forms
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if(!curacro) {
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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
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if(curchars <= 4) {
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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. If >= 5 letters allow 1 changed letter, if >=8 letters allow also 1 (Levenshtein distance)
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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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# 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 <- readLines("issues.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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tagexpand <- c("", "s", "n", "en", "er", "e")
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# Parallelisation
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writeLines(c(""), "issuecomp-analysis.log")
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cl<-makeCluster(4)
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registerDoParallel(cl)
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df<-foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
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#for(d in 1:nrow(issues)) {
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# Go through every day
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curdate <- issues$date[d]
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cat(paste(as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
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# Put all tweets from specific day in a temporary DF
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tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
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for(t in 1:nrow(tweets_curday)){
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cat(paste("Starting tweet", t, "of",as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
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# Select tweet's text, make it lowercase and remove hashtag indicators (#)
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curtext <- as.character(tweets_curday$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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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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# Now expand the current tag by possible suffixes that may be plural forms
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if(!curacro) {
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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
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if(curchars <= 4) {
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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. If >= 5 letters allow 1 changed letter, if >=8 letters allow also 1 (Levenshtein distance)
|
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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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df
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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 <- readLines("issues.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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@@ -510,3 +173,340 @@ else {
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} # /for issuelist
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||||
} # /for tweets_curday
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||||
} # /for drange
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require(lubridate)
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||||
require(XML)
|
||||
require(ggplot2)
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||||
require(reshape2)
|
||||
require(stringr)
|
||||
library(foreach)
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library(doParallel)
|
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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 <- readLines("issues.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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tagexpand <- c("", "s", "n", "en", "er", "e")
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||||
# Parallelisation
|
||||
writeLines(c(""), "issuecomp-analysis.log")
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||||
cl<-makeCluster(4)
|
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registerDoParallel(cl)
|
||||
foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
|
||||
#for(d in 1:nrow(issues)) {
|
||||
# Go through every day
|
||||
curdate <- issues$date[d]
|
||||
cat(paste(as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# Put all tweets from specific day in a temporary DF
|
||||
tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
|
||||
for(t in 1:nrow(tweets_curday)){
|
||||
# cat(paste("Starting tweet", t, "of",as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# Select tweet's text, make it lowercase and remove hashtag indicators (#)
|
||||
curtext <- as.character(tweets_curday$text[t])
|
||||
curtext <- str_replace_all(curtext, "#", "")
|
||||
curid <- as.character(tweets_curday$id_str[t])
|
||||
# Now test each single issue (not tag!)
|
||||
for(i in 1:length(issueheads)) {
|
||||
curissue <- issueheads[i]
|
||||
curtags <- as.character(issuelist[[curissue]])
|
||||
curfile <- str_c(id_folder,"/",curissue,".csv")
|
||||
# Now test all tags of a single issue
|
||||
for(s in 1:length(curtags)) {
|
||||
curtag <- curtags[s]
|
||||
curchars <- nchar(curtag, type = "chars")
|
||||
# Check if tag is an acronym. If so, ignore.case will be deactivated in smartPatternMatch
|
||||
if(curchars <= 4) {
|
||||
curacro <- checkAcronym(string = curtag, chars = curchars)
|
||||
} else {
|
||||
curacro <- FALSE
|
||||
}
|
||||
# Now expand the current tag by possible suffixes that may be plural forms
|
||||
if(!curacro) {
|
||||
for(e in 1:length(tagexpand)) {
|
||||
curtag[e] <- str_c(curtag[1], tagexpand[e])
|
||||
}
|
||||
}
|
||||
# Set Levenshtein distance depending on char length
|
||||
if(curchars <= 4) {
|
||||
curdistance <- 0
|
||||
} else {
|
||||
curdistance <- 1
|
||||
}
|
||||
# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow also 1 (Levenshtein distance)
|
||||
tags_found <- NULL
|
||||
# Match the tweet with each variation of tagexpand
|
||||
for(e in 1:length(curtag)) {
|
||||
tags_found[e] <- smartPatternMatch(curtext, curtag[e], curdistance, curacro)
|
||||
}
|
||||
tags_found <- any(tags_found)
|
||||
curtag <- curtag[1]
|
||||
if(tags_found == TRUE) {
|
||||
# # Raise number of findings on this day for this issue by 1
|
||||
# issues[d,curissue] <- issues[d,curissue] + 1
|
||||
#
|
||||
# # Add issue and first matched tag of tweet to tweets-DF
|
||||
# oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
|
||||
# tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
|
||||
# oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
|
||||
# tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
|
||||
# Add information to file for function viewPatternMatching
|
||||
write(str_c(curdate,";\"",curid,"\";",curissue,";",curtag), curfile, append = TRUE)
|
||||
# cat(paste("Match!\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# data.frame(date=curdate, issue=curissue)
|
||||
break # next issue, no more tags from same issue
|
||||
}
|
||||
else {
|
||||
#cat("Nothing found\n")
|
||||
}
|
||||
} # /for curtags
|
||||
} # /for issuelist
|
||||
} # /for tweets_curday
|
||||
} # /for drange
|
||||
stopCluster(cl)
|
||||
drange
|
||||
drange[40]
|
||||
drange[50]
|
||||
View(issues)
|
||||
require(lubridate)
|
||||
require(XML)
|
||||
require(ggplot2)
|
||||
require(reshape2)
|
||||
require(stringr)
|
||||
library(foreach)
|
||||
library(doParallel)
|
||||
drange[70]
|
||||
drange[80]
|
||||
drange[90]
|
||||
cl<-makeCluster(4)
|
||||
registerDoParallel(cl)
|
||||
foreach(d = 51:90, .packages = c("stringr"), .combine=rbind) %dopar% {
|
||||
#for(d in 1:nrow(issues)) {
|
||||
# Go through every day
|
||||
curdate <- issues$date[d]
|
||||
cat(paste(as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# Put all tweets from specific day in a temporary DF
|
||||
tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
|
||||
for(t in 1:nrow(tweets_curday)){
|
||||
# cat(paste("Starting tweet", t, "of",as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# Select tweet's text, make it lowercase and remove hashtag indicators (#)
|
||||
curtext <- as.character(tweets_curday$text[t])
|
||||
curtext <- str_replace_all(curtext, "#", "")
|
||||
curid <- as.character(tweets_curday$id_str[t])
|
||||
# Now test each single issue (not tag!)
|
||||
for(i in 1:length(issueheads)) {
|
||||
curissue <- issueheads[i]
|
||||
curtags <- as.character(issuelist[[curissue]])
|
||||
curfile <- str_c(id_folder,"/",curissue,".csv")
|
||||
# Now test all tags of a single issue
|
||||
for(s in 1:length(curtags)) {
|
||||
curtag <- curtags[s]
|
||||
curchars <- nchar(curtag, type = "chars")
|
||||
# Check if tag is an acronym. If so, ignore.case will be deactivated in smartPatternMatch
|
||||
if(curchars <= 4) {
|
||||
curacro <- checkAcronym(string = curtag, chars = curchars)
|
||||
} else {
|
||||
curacro <- FALSE
|
||||
}
|
||||
# Now expand the current tag by possible suffixes that may be plural forms
|
||||
if(!curacro) {
|
||||
for(e in 1:length(tagexpand)) {
|
||||
curtag[e] <- str_c(curtag[1], tagexpand[e])
|
||||
}
|
||||
}
|
||||
# Set Levenshtein distance depending on char length
|
||||
if(curchars <= 4) {
|
||||
curdistance <- 0
|
||||
} else {
|
||||
curdistance <- 1
|
||||
}
|
||||
# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow also 1 (Levenshtein distance)
|
||||
tags_found <- NULL
|
||||
# Match the tweet with each variation of tagexpand
|
||||
for(e in 1:length(curtag)) {
|
||||
tags_found[e] <- smartPatternMatch(curtext, curtag[e], curdistance, curacro)
|
||||
}
|
||||
tags_found <- any(tags_found)
|
||||
curtag <- curtag[1]
|
||||
if(tags_found == TRUE) {
|
||||
# # Raise number of findings on this day for this issue by 1
|
||||
# issues[d,curissue] <- issues[d,curissue] + 1
|
||||
#
|
||||
# # Add issue and first matched tag of tweet to tweets-DF
|
||||
# oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
|
||||
# tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
|
||||
# oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
|
||||
# tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
|
||||
# Add information to file for function viewPatternMatching
|
||||
write(str_c(curdate,";\"",curid,"\";",curissue,";",curtag), curfile, append = TRUE)
|
||||
# cat(paste("Match!\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# data.frame(date=curdate, issue=curissue)
|
||||
break # next issue, no more tags from same issue
|
||||
}
|
||||
else {
|
||||
#cat("Nothing found\n")
|
||||
}
|
||||
} # /for curtags
|
||||
} # /for issuelist
|
||||
} # /for tweets_curday
|
||||
} # /for drange
|
||||
#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)
|
||||
stopCluster(cl)
|
||||
drange[121]
|
||||
cl<-makeCluster(4)
|
||||
registerDoParallel(cl)
|
||||
foreach(d = 91:120, .packages = c("stringr"), .combine=rbind) %dopar% {
|
||||
#for(d in 1:nrow(issues)) {
|
||||
# Go through every day
|
||||
curdate <- issues$date[d]
|
||||
cat(paste(as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# Put all tweets from specific day in a temporary DF
|
||||
tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
|
||||
for(t in 1:nrow(tweets_curday)){
|
||||
# cat(paste("Starting tweet", t, "of",as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# Select tweet's text, make it lowercase and remove hashtag indicators (#)
|
||||
curtext <- as.character(tweets_curday$text[t])
|
||||
curtext <- str_replace_all(curtext, "#", "")
|
||||
curid <- as.character(tweets_curday$id_str[t])
|
||||
# Now test each single issue (not tag!)
|
||||
for(i in 1:length(issueheads)) {
|
||||
curissue <- issueheads[i]
|
||||
curtags <- as.character(issuelist[[curissue]])
|
||||
curfile <- str_c(id_folder,"/",curissue,".csv")
|
||||
# Now test all tags of a single issue
|
||||
for(s in 1:length(curtags)) {
|
||||
curtag <- curtags[s]
|
||||
curchars <- nchar(curtag, type = "chars")
|
||||
# Check if tag is an acronym. If so, ignore.case will be deactivated in smartPatternMatch
|
||||
if(curchars <= 4) {
|
||||
curacro <- checkAcronym(string = curtag, chars = curchars)
|
||||
} else {
|
||||
curacro <- FALSE
|
||||
}
|
||||
# Now expand the current tag by possible suffixes that may be plural forms
|
||||
if(!curacro) {
|
||||
for(e in 1:length(tagexpand)) {
|
||||
curtag[e] <- str_c(curtag[1], tagexpand[e])
|
||||
}
|
||||
}
|
||||
# Set Levenshtein distance depending on char length
|
||||
if(curchars <= 4) {
|
||||
curdistance <- 0
|
||||
} else {
|
||||
curdistance <- 1
|
||||
}
|
||||
# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow also 1 (Levenshtein distance)
|
||||
tags_found <- NULL
|
||||
# Match the tweet with each variation of tagexpand
|
||||
for(e in 1:length(curtag)) {
|
||||
tags_found[e] <- smartPatternMatch(curtext, curtag[e], curdistance, curacro)
|
||||
}
|
||||
tags_found <- any(tags_found)
|
||||
curtag <- curtag[1]
|
||||
if(tags_found == TRUE) {
|
||||
# # Raise number of findings on this day for this issue by 1
|
||||
# issues[d,curissue] <- issues[d,curissue] + 1
|
||||
#
|
||||
# # Add issue and first matched tag of tweet to tweets-DF
|
||||
# oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
|
||||
# tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
|
||||
# oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
|
||||
# tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
|
||||
# Add information to file for function viewPatternMatching
|
||||
write(str_c(curdate,";\"",curid,"\";",curissue,";",curtag), curfile, append = TRUE)
|
||||
# cat(paste("Match!\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# data.frame(date=curdate, issue=curissue)
|
||||
break # next issue, no more tags from same issue
|
||||
}
|
||||
else {
|
||||
#cat("Nothing found\n")
|
||||
}
|
||||
} # /for curtags
|
||||
} # /for issuelist
|
||||
} # /for tweets_curday
|
||||
} # /for drange
|
||||
stopCluster(cl)
|
||||
drange[102]
|
||||
require(lubridate)
|
||||
require(XML)
|
||||
require(ggplot2)
|
||||
require(reshape2)
|
||||
require(stringr)
|
||||
library(foreach)
|
||||
library(doParallel)
|
||||
cl<-makeCluster(4)
|
||||
registerDoParallel(cl)
|
||||
foreach(d = 101:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
|
||||
#for(d in 1:nrow(issues)) {
|
||||
# Go through every day
|
||||
curdate <- issues$date[d]
|
||||
cat(paste(as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# Put all tweets from specific day in a temporary DF
|
||||
tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
|
||||
for(t in 1:nrow(tweets_curday)){
|
||||
# cat(paste("Starting tweet", t, "of",as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# Select tweet's text, make it lowercase and remove hashtag indicators (#)
|
||||
curtext <- as.character(tweets_curday$text[t])
|
||||
curtext <- str_replace_all(curtext, "#", "")
|
||||
curid <- as.character(tweets_curday$id_str[t])
|
||||
# Now test each single issue (not tag!)
|
||||
for(i in 1:length(issueheads)) {
|
||||
curissue <- issueheads[i]
|
||||
curtags <- as.character(issuelist[[curissue]])
|
||||
curfile <- str_c(id_folder,"/",curissue,".csv")
|
||||
# Now test all tags of a single issue
|
||||
for(s in 1:length(curtags)) {
|
||||
curtag <- curtags[s]
|
||||
curchars <- nchar(curtag, type = "chars")
|
||||
# Check if tag is an acronym. If so, ignore.case will be deactivated in smartPatternMatch
|
||||
if(curchars <= 4) {
|
||||
curacro <- checkAcronym(string = curtag, chars = curchars)
|
||||
} else {
|
||||
curacro <- FALSE
|
||||
}
|
||||
# Now expand the current tag by possible suffixes that may be plural forms
|
||||
if(!curacro) {
|
||||
for(e in 1:length(tagexpand)) {
|
||||
curtag[e] <- str_c(curtag[1], tagexpand[e])
|
||||
}
|
||||
}
|
||||
# Set Levenshtein distance depending on char length
|
||||
if(curchars <= 4) {
|
||||
curdistance <- 0
|
||||
} else {
|
||||
curdistance <- 1
|
||||
}
|
||||
# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow also 1 (Levenshtein distance)
|
||||
tags_found <- NULL
|
||||
# Match the tweet with each variation of tagexpand
|
||||
for(e in 1:length(curtag)) {
|
||||
tags_found[e] <- smartPatternMatch(curtext, curtag[e], curdistance, curacro)
|
||||
}
|
||||
tags_found <- any(tags_found)
|
||||
curtag <- curtag[1]
|
||||
if(tags_found == TRUE) {
|
||||
# # Raise number of findings on this day for this issue by 1
|
||||
# issues[d,curissue] <- issues[d,curissue] + 1
|
||||
#
|
||||
# # Add issue and first matched tag of tweet to tweets-DF
|
||||
# oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
|
||||
# tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
|
||||
# oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
|
||||
# tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
|
||||
# Add information to file for function viewPatternMatching
|
||||
write(str_c(curdate,";\"",curid,"\";",curissue,";",curtag), curfile, append = TRUE)
|
||||
# cat(paste("Match!\n"), file="issuecomp-analysis.log", append=TRUE)
|
||||
# data.frame(date=curdate, issue=curissue)
|
||||
break # next issue, no more tags from same issue
|
||||
}
|
||||
else {
|
||||
#cat("Nothing found\n")
|
||||
}
|
||||
} # /for curtags
|
||||
} # /for issuelist
|
||||
} # /for tweets_curday
|
||||
} # /for drange
|
||||
|
||||
@@ -21,8 +21,8 @@ drange <- date_start + days(0:drange)
|
||||
# MATCH TWEETS ------------------------------------------------------------
|
||||
|
||||
id_folder <- "matched-ids"
|
||||
unlink(id_folder, recursive = TRUE)
|
||||
dir.create(id_folder)
|
||||
#unlink(id_folder, recursive = TRUE)
|
||||
#dir.create(id_folder)
|
||||
|
||||
issues <- data.frame(date = drange)
|
||||
issuelist <- readLines("issues.xml")
|
||||
@@ -37,10 +37,10 @@ tagexpand <- c("", "s", "n", "en", "er", "e")
|
||||
|
||||
# Parallelisation
|
||||
writeLines(c(""), "issuecomp-analysis.log")
|
||||
cl<-makeCluster(4)
|
||||
cl<-makeCluster(3)
|
||||
registerDoParallel(cl)
|
||||
|
||||
foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
|
||||
foreach(d = 101:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
|
||||
#for(d in 1:nrow(issues)) {
|
||||
# Go through every day
|
||||
curdate <- issues$date[d]
|
||||
|
||||
+105
-22
@@ -3,25 +3,108 @@
|
||||
2014-01-02
|
||||
2014-01-03
|
||||
2014-01-04
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
Match!
|
||||
2014-01-05
|
||||
2014-01-06
|
||||
2014-01-07
|
||||
2014-01-08
|
||||
2014-01-09
|
||||
2014-01-10
|
||||
2014-01-11
|
||||
2014-01-12
|
||||
2014-01-13
|
||||
2014-01-14
|
||||
2014-01-15
|
||||
2014-01-16
|
||||
2014-01-17
|
||||
2014-01-18
|
||||
2014-01-19
|
||||
2014-01-20
|
||||
2014-01-21
|
||||
2014-01-22
|
||||
2014-01-23
|
||||
2014-01-24
|
||||
2014-01-25
|
||||
2014-01-26
|
||||
2014-01-27
|
||||
2014-01-28
|
||||
2014-01-29
|
||||
2014-01-30
|
||||
2014-01-31
|
||||
2014-02-01
|
||||
2014-02-02
|
||||
2014-02-03
|
||||
2014-02-04
|
||||
2014-02-05
|
||||
2014-02-06
|
||||
2014-02-07
|
||||
2014-02-08
|
||||
2014-02-09
|
||||
2014-02-10
|
||||
2014-02-11
|
||||
2014-02-12
|
||||
2014-02-13
|
||||
2014-02-14
|
||||
2014-02-15
|
||||
2014-02-16
|
||||
2014-02-17
|
||||
2014-02-18
|
||||
2014-02-19
|
||||
2014-02-20
|
||||
2014-02-21
|
||||
2014-02-22
|
||||
2014-02-23
|
||||
2014-02-20
|
||||
2014-02-21
|
||||
2014-02-22
|
||||
2014-02-23
|
||||
2014-02-24
|
||||
2014-02-25
|
||||
2014-02-26
|
||||
2014-02-27
|
||||
2014-02-28
|
||||
2014-03-01
|
||||
2014-03-02
|
||||
2014-03-03
|
||||
2014-03-04
|
||||
2014-03-05
|
||||
2014-03-06
|
||||
2014-03-07
|
||||
2014-03-08
|
||||
2014-03-09
|
||||
2014-03-10
|
||||
2014-03-11
|
||||
2014-03-12
|
||||
2014-03-13
|
||||
2014-03-14
|
||||
2014-03-15
|
||||
2014-03-16
|
||||
2014-03-17
|
||||
2014-03-18
|
||||
2014-03-19
|
||||
2014-03-20
|
||||
2014-03-21
|
||||
2014-03-22
|
||||
2014-03-23
|
||||
2014-03-24
|
||||
2014-03-25
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2014-03-26
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2014-03-27
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2014-03-28
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2014-03-29
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2014-03-30
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2014-03-31
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2014-04-01
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2014-04-02
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2014-04-03
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2014-04-04
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2014-04-05
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2014-04-06
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2014-04-07
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2014-04-08
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2014-04-09
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2014-04-10
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2014-04-11
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2014-04-12
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2014-04-13
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2014-04-14
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2014-04-15
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Reference in New Issue
Block a user