ongoing categorisation

2015-02-23 02:06:01 +01:00
parent d7de9dda0c
commit eaffcf3db2
4 changed files with 446 additions and 363 deletions
@@ -1,340 +1,3 @@
 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
 # MATCH TWEETS ------------------------------------------------------------
 id_folder <- "matched-ids"
 unlink(id_folder, recursive = TRUE)
 dir.create(id_folder)
 issues <- data.frame(date = drange)
 issuelist <- readLines("issues.xml")
 issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
 issuelist <- xmlToList(issuelist)
 issueheads <- names(issuelist)
 issues[issueheads] <- 0
 tweets$issue <- ""
 tweets$tags <- ""
 tagexpand <- c("", "s", "n", "en", "er", "e")
 # Parallelisation
 writeLines(c(""), "issuecomp-analysis.log")
 cl<-makeCluster(4)
 registerDoParallel(cl)
 df<-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
 #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)
 require(lubridate)
 require(XML)
 require(ggplot2)
 require(reshape2)
 require(stringr)
 library(foreach)
 library(doParallel)
 source("issuecomp-functions.R")
 load(file = "tweets_untagged.RData")
 # Create date range
 date_start <- as.Date("2014-01-01")
 date_end <- as.Date("2014-12-31")
 drange <- as.integer(date_end - date_start)
 drange <- date_start + days(0:drange)
 # MATCH TWEETS ------------------------------------------------------------
 id_folder <- "matched-ids"
 unlink(id_folder, recursive = TRUE)
 dir.create(id_folder)
 issues <- data.frame(date = drange)
 issuelist <- readLines("issues.xml")
 issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
 issuelist <- xmlToList(issuelist)
 issueheads <- names(issuelist)
 issues[issueheads] <- 0
 tweets$issue <- ""
 tweets$tags <- ""
 tagexpand <- c("", "s", "n", "en", "er", "e")
 # Parallelisation
 writeLines(c(""), "issuecomp-analysis.log")
 cl<-makeCluster(4)
 registerDoParallel(cl)
 df<-foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
 #for(d in 1:nrow(issues)) {
 # Go through every day
 curdate <- issues$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
 # MATCH TWEETS ------------------------------------------------------------
 id_folder <- "matched-ids"
 unlink(id_folder, recursive = TRUE)
 dir.create(id_folder)
 issues <- data.frame(date = drange)
 issuelist <- readLines("issues.xml")
 issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
 issuelist <- xmlToList(issuelist)
 issueheads <- names(issuelist)
 issues[issueheads] <- 0
 tweets$issue <- ""
 tweets$tags <- ""
 tagexpand <- c("", "s", "n", "en", "er", "e")
 # Parallelisation
 writeLines(c(""), "issuecomp-analysis.log")
 cl<-makeCluster(4)
 registerDoParallel(cl)
 df<-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
 df
 # MATCH TWEETS ------------------------------------------------------------
 id_folder <- "matched-ids"
 unlink(id_folder, recursive = TRUE)
 dir.create(id_folder)
 issues <- data.frame(date = drange)
 issuelist <- readLines("issues.xml")
 issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
 issuelist <- xmlToList(issuelist)
 issueheads <- names(issuelist)
 issues[issueheads] <- 0
 tweets$issue <- ""
@@ -510,3 +173,340 @@ else {
 } # /for issuelist
 } # /for tweets_curday
 } # /for drange
 require(lubridate)
 require(XML)
 require(ggplot2)
 require(reshape2)
 require(stringr)
 library(foreach)
 library(doParallel)
 # MATCH TWEETS ------------------------------------------------------------
 id_folder <- "matched-ids"
 unlink(id_folder, recursive = TRUE)
 dir.create(id_folder)
 issues <- data.frame(date = drange)
 issuelist <- readLines("issues.xml")
 issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
 issuelist <- xmlToList(issuelist)
 issueheads <- names(issuelist)
 issues[issueheads] <- 0
 tweets$issue <- ""
 tweets$tags <- ""
 tagexpand <- c("", "s", "n", "en", "er", "e")
 # Parallelisation
 writeLines(c(""), "issuecomp-analysis.log")
 cl<-makeCluster(4)
 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)
+#unlink(id_folder, recursive = TRUE)
-dir.create(id_folder)
+#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]
@@ -3,25 +3,108 @@
 2014-01-02 
 2014-01-03 
 2014-01-04 
-Match!
+2014-01-05 
-Match!
+2014-01-06 
-Match!
+2014-01-07 
-Match!
+2014-01-08 
-Match!
+2014-01-09 
-Match!
+2014-01-10 
-Match!
+2014-01-11 
-Match!
+2014-01-12 
-Match!
+2014-01-13 
-Match!
+2014-01-14 
-Match!
+2014-01-15 
-Match!
+2014-01-16 
-Match!
+2014-01-17 
-Match!
+2014-01-18 
-Match!
+2014-01-19 
-Match!
+2014-01-20 
-Match!
+2014-01-21 
-Match!
+2014-01-22 
-Match!
+2014-01-23 
-Match!
+2014-01-24 
-Match!
+2014-01-25 
-Match!
+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 
 2014-03-26 
 2014-03-27 
 2014-03-28 
 2014-03-29 
 2014-03-30 
 2014-03-31 
 2014-04-01 
 2014-04-02 
 2014-04-03 
 2014-04-04 
 2014-04-05 
 2014-04-06 
 2014-04-07 
 2014-04-08 
 2014-04-09 
 2014-04-10 
 2014-04-11 
 2014-04-12 
 2014-04-13 
 2014-04-14 
 2014-04-15
 -01-02
 -01-03
 -01-04
-Match!
+-01-05
-Match!
+-01-06
-Match!
+-01-07
-Match!
+-01-08
-Match!
+-01-09
-Match!
+-01-10
-Match!
+-01-11
-Match!
+-01-12
-Match!
+-01-13
-Match!
+-01-14
-Match!
+-01-15
-Match!
+-01-16
-Match!
+-01-17
-Match!
+-01-18
-Match!
+-01-19
-Match!
+-01-20
-Match!
+-01-21
-Match!
+-01-22
-Match!
+-01-23
-Match!
+-01-24
-Match!
+-01-25
-Match!
+-01-26
+-01-27
+-01-28
+-01-29
+-01-30
+-01-31
+-02-01
+-02-02
+-02-03
+-02-04
+-02-05
+-02-06
+-02-07
+-02-08
+-02-09
+-02-10
+-02-11
+-02-12
+-02-13
+-02-14
+-02-15
+-02-16
+-02-17
+-02-18
+-02-19
+-02-20
+-02-21
+-02-22
+-02-23
+-02-20
+-02-21
+-02-22
+-02-23
+-02-24
+-02-25
+-02-26
+-02-27
+-02-28
+-03-01
+-03-02
+-03-03
+-03-04
+-03-05
+-03-06
+-03-07
+-03-08
+-03-09
+-03-10
+-03-11
+-03-12
+-03-13
+-03-14
+-03-15
+-03-16
+-03-17
+-03-18
+-03-19
+-03-20
+-03-21
+-03-22
+-03-23
+-03-24
+-03-25
+-03-26
+-03-27
+-03-28
+-03-29
+-03-30
+-03-31
+-04-01
+-04-02
+-04-03
+-04-04
+-04-05
+-04-06
+-04-07
+-04-08
+-04-09
+-04-10
+-04-11
+-04-12
+-04-13
+-04-14
+-04-15