improve parallel

.Rhistory

@@ -1,317 +1,3 @@
-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,"\";",curtag), curfile, append = TRUE)
-cat("Match!\n")
-break
-}
-else {
-#cat("Nothing found\n")
-}
-} # /for curtags
-} # /for issuelist
-} # /for tweets_curday
-} # /for drange
-stopCluster(cl)
-View(issues)
-cl
-df
-View(data)
-stopCluster(cl)
-# 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")
-# Parallelisation
-writeLines(c(""), "issuecomp-analysis.log")
-cl<-makeCluster(3)
-registerDoParallel(cl)
-df<-foreach(d = 1:nrow(issues), .packages = c("stringr")) %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,"\";",curtag), curfile, append = TRUE)
-cat("Match!\n")
-break
-}
-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)
-# 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$tags <- ""
-tagexpand <- c("", "s", "n", "en", "er")
-# Parallelisation
-writeLines(c(""), "issuecomp-analysis.log")
-cl<-makeCluster(3)
-registerDoParallel(cl)
-df<-foreach(d = 1:nrow(issues), .packages = c("stringr")) %dopar% {
-#for(d in 1:nrow(issues)) {
-# Go through every day
-curdate <- issues$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,"\";",curtag), curfile, append = TRUE)
-cat("Match!\n")
-break
-}
-else {
-#cat("Nothing found\n")
-}
-} # /for curtags
-} # /for issuelist
-} # /for tweets_curday
-} # /for drange
-stopCluster(cl)
-cl<-makeCluster(3)
-registerDoParallel(cl)
-stopCluster(cl)
-# 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")
-# Parallelisation
-writeLines(c(""), "issuecomp-analysis.log")
-cl<-makeCluster(3)
-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,"\";",curtag), curfile, append = TRUE)
-cat("Match!\n")
-break
-}
-else {
-#cat("Nothing found\n")
-}
 } # /for curtags
 } # /for issuelist
 } # /for tweets_curday
@@ -510,3 +196,317 @@ stopCluster(cl)
 View(issues)
 rm(data)
 df
+require(lubridate)
+require(XML)
+require(ggplot2)
+require(reshape2)
+require(stringr)
+library(foreach)
+library(doParallel)
+View(issues)
+# 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$tags <- ""
+tagexpand <- c("", "s", "n", "en", "er")
+# Parallelisation
+writeLines(c(""), "issuecomp-analysis.log")
+cl<-makeCluster(3)
+registerDoParallel(cl)
+df<-foreach(d = 1:3, .packages = c("stringr"), .combine=rbind) %dopar% {
+#df<-foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
+#for(d in 1:nrow(issues)) {
+# Go through every day
+curdate <- issues$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 1:25){
+#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,"\";",curtag), curfile, append = TRUE)
+cat(paste("Match!\n"), file="issuecomp-analysis.log", append=TRUE)
+data.frame(date=curdate, issue=curissue)
+break
+}
+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)
+df
+drange
+nrow(tweets[tweets[, "id_str"] == curid, "issue"])
+curid
+nrow(tweets[tweets[, "date"] == 2014-01-10, "issue"])
+nrow(tweets[tweets[, "created_at"] == 2014-01-10, "issue"])
+View(tweets)
+tweets[tweets[, "created_at"] == 2014-01-10, "issue"]
+tweets[tweets[, "created_at"] == 2014-01-10, ]
+tweets[tweets[, "created_at"] == "2014-01-10", ]
+tweets[tweets[, "created_at"] == "2014-01-10", "user"]
+nrow(tweets[tweets[, "created_at"] == "2014-01-10", "user"])
+nrow(tweets[tweets[, "created_at"] == "2014-01-10", "id_str"])
+length(tweets[tweets[, "created_at"] == "2014-01-10", "id_str"])
+writeLines(c(""), "issuecomp-analysis.log")
+cl<-makeCluster(3)
+registerDoParallel(cl)
+df<-foreach(d = 1:length(drange), .packages = c("stringr"), .combine=rbind) %dopar% {
+curdate <- as.character(drange[d])
+curissue <- length(tweets[tweets[, "created_at"] == curdate, "id_str"])
+data.frame(date=curdate, tweets=curissue)
+}
+stopCluster(cl)
+View(df)
+writeLines(c(""), "issuecomp-analysis.log")
+cl<-makeCluster(3)
+registerDoParallel(cl)
+df<-foreach(d = 1:length(drange), .packages = c("stringr"), .combine=rbind) %dopar% {
+for(i in 1:5) {
+curdate <- as.character(drange[d])
+curissue <- length(tweets[tweets[, "created_at"] == curdate, "id_str"])
+data.frame(date=curdate, tweets=curissue)
+}
+}
+stopCluster(cl)
+View(tweets)
+curissue
+curtag
+# 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(3)
+registerDoParallel(cl)
+df<-foreach(d = 1:3, .packages = c("stringr"), .combine=rbind) %dopar% {
+#df<-foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
+#for(d in 1:nrow(issues)) {
+# Go through every day
+curdate <- issues$date[d]
+cat(paste(as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
+# Put all tweets from specific day in a temporary DF
+tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
+for(t in 1:25){
+#for(t in 1:nrow(tweets_curday)){
+cat(paste("Starting tweet", t, "of",as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
+# Select tweet's text, make it lowercase and remove hashtag indicators (#)
+curtext <- as.character(tweets_curday$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)
+# 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$tags <- ""
+tagexpand <- c("", "s", "n", "en", "er", "e")
+# Parallelisation
+writeLines(c(""), "issuecomp-analysis.log")
+cl<-makeCluster(3)
+registerDoParallel(cl)
+df<-foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
+#for(d in 1:nrow(issues)) {
+# Go through every day
+curdate <- issues$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

.gitignore

@@ -4,3 +4,4 @@ tweets_untagged.csv
 tweets_untagged.RData
 .RData
 matched-ids
+issuecomp-analysis.log

issuecomp-analysis.R

@@ -33,15 +33,14 @@ issues[issueheads] <- 0
 tweets$issue <- ""
 tweets$tags <- ""
 
-tagexpand <- c("", "s", "n", "en", "er")
+tagexpand <- c("", "s", "n", "en", "er", "e")
 
 # Parallelisation
 writeLines(c(""), "issuecomp-analysis.log")  
-cl<-makeCluster(3)
+cl<-makeCluster(4)
 registerDoParallel(cl)
 
-df<-foreach(d = 1:3, .packages = c("stringr"), .combine=rbind) %dopar% {
+df<-foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
-#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]
@@ -50,8 +49,7 @@ df<-foreach(d = 1:3, .packages = c("stringr"), .combine=rbind) %dopar% {
   # Put all tweets from specific day in a temporary DF
   tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
   
-  for(t in 1:25){
+  for(t in 1:nrow(tweets_curday)){
-  #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])
@@ -101,25 +99,25 @@ df<-foreach(d = 1:3, .packages = c("stringr"), .combine=rbind) %dopar% {
         curtag <- curtag[1]
         
         if(tags_found == TRUE) {
-          # Raise number of findings on this day for this issue by 1
+#           # Raise number of findings on this day for this issue by 1
-          issues[d,curissue] <- issues[d,curissue] + 1
+#           issues[d,curissue] <- issues[d,curissue] + 1
-          
+#           
-          # Add issue and first matched tag of tweet to tweets-DF
+#           # Add issue and first matched tag of tweet to tweets-DF
-          oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
+#           oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
-          tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
+#           tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
-          oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
+#           oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
-          tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
+#           tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
           
           # Add information to file for function viewPatternMatching
-          write(str_c(curdate,";\"",curid,"\";",curtag), curfile, append = TRUE)
+          write(str_c(curdate,";\"",curid,"\";",curissue,";",curtag), curfile, append = TRUE)
           cat(paste("Match!\n"), file="issuecomp-analysis.log", append=TRUE)
-          break
+#           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

issuecomp-analysis.log

@@ -1,103 +1,76 @@
 
-2014-01-01 
 2014-01-02 
+2014-01-01 
 2014-01-03 
 Starting tweet 1 of 2014-01-03 
 Starting tweet 1 of 2014-01-01 
 Starting tweet 1 of 2014-01-02 
 Starting tweet 2 of 2014-01-01 
-Starting tweet 2 of 2014-01-03 
 Starting tweet 2 of 2014-01-02 
-Starting tweet 3 of 2014-01-03 
+Starting tweet 2 of 2014-01-03 
 Starting tweet 3 of 2014-01-01 
 Match!
 Starting tweet 3 of 2014-01-02 
+Starting tweet 3 of 2014-01-03 
+Starting tweet 4 of 2014-01-02 
+Starting tweet 4 of 2014-01-01 
 Starting tweet 4 of 2014-01-03 
 Match!
-Starting tweet 4 of 2014-01-01 
 Match!
-Starting tweet 4 of 2014-01-02 
-Starting tweet 5 of 2014-01-03 
-Starting tweet 5 of 2014-01-01 
-Starting tweet 6 of 2014-01-03 
 Match!
 Starting tweet 5 of 2014-01-02 
-Match!
+Starting tweet 5 of 2014-01-01 
-Starting tweet 6 of 2014-01-01 
+Starting tweet 5 of 2014-01-03 
 Starting tweet 6 of 2014-01-02 
-Starting tweet 7 of 2014-01-03 
+Starting tweet 6 of 2014-01-01 
-Starting tweet 7 of 2014-01-01 
+Starting tweet 6 of 2014-01-03 
+Match!
 Match!
 Starting tweet 7 of 2014-01-02 
-Starting tweet 8 of 2014-01-03 
+Starting tweet 7 of 2014-01-01 
+Starting tweet 7 of 2014-01-03 
 Starting tweet 8 of 2014-01-01 
-Match!
 Starting tweet 8 of 2014-01-02 
-Starting tweet 9 of 2014-01-03 
+Starting tweet 8 of 2014-01-03 
+Match!
 Starting tweet 9 of 2014-01-01 
 Starting tweet 9 of 2014-01-02 
-Starting tweet 10 of 2014-01-03 
+Starting tweet 9 of 2014-01-03 
 Starting tweet 10 of 2014-01-01 
 Starting tweet 10 of 2014-01-02 
-Match!
+Starting tweet 10 of 2014-01-03 
-Starting tweet 11 of 2014-01-03 
 Starting tweet 11 of 2014-01-01 
 Starting tweet 11 of 2014-01-02 
-Starting tweet 12 of 2014-01-03 
+Match!
+Starting tweet 11 of 2014-01-03 
 Starting tweet 12 of 2014-01-01 
 Starting tweet 12 of 2014-01-02 
-Starting tweet 13 of 2014-01-03 
+Starting tweet 12 of 2014-01-03 
-Match!
 Starting tweet 13 of 2014-01-01 
+Match!
 Starting tweet 13 of 2014-01-02 
-Starting tweet 14 of 2014-01-03 
+Starting tweet 13 of 2014-01-03 
 Starting tweet 14 of 2014-01-01 
 Starting tweet 14 of 2014-01-02 
-Match!
+Starting tweet 14 of 2014-01-03 
-Starting tweet 15 of 2014-01-03 
 Starting tweet 15 of 2014-01-01 
 Match!
 Starting tweet 15 of 2014-01-02 
 Match!
-Starting tweet 16 of 2014-01-03 
+Starting tweet 15 of 2014-01-03 
 Starting tweet 16 of 2014-01-01 
 Starting tweet 16 of 2014-01-02 
+Match!
+Starting tweet 16 of 2014-01-03 
+Starting tweet 17 of 2014-01-01 
+Match!
+Starting tweet 17 of 2014-01-02 
 Starting tweet 17 of 2014-01-03 
 Match!
-Starting tweet 17 of 2014-01-01 
+Starting tweet 18 of 2014-01-01 
-Starting tweet 17 of 2014-01-02 
 Match!
 Starting tweet 18 of 2014-01-03 
 Match!
-Match!
 Starting tweet 18 of 2014-01-02 
 Match!
-Starting tweet 18 of 2014-01-01 
-Starting tweet 19 of 2014-01-03 
-Match!
-Starting tweet 19 of 2014-01-02 
 Starting tweet 19 of 2014-01-01 
-Match!
-Starting tweet 20 of 2014-01-03 
-Starting tweet 20 of 2014-01-02 
-Match!
-Starting tweet 20 of 2014-01-01 
-Match!
-Starting tweet 21 of 2014-01-03 
-Starting tweet 21 of 2014-01-02 
-Match!
-Starting tweet 21 of 2014-01-01 
-Starting tweet 22 of 2014-01-03 
-Starting tweet 22 of 2014-01-02 
-Starting tweet 22 of 2014-01-01 
-Starting tweet 23 of 2014-01-03 
-Starting tweet 23 of 2014-01-02 
-Starting tweet 23 of 2014-01-01 
-Starting tweet 24 of 2014-01-03 
-Starting tweet 24 of 2014-01-02 
-Starting tweet 24 of 2014-01-01 
-Match!
-Starting tweet 25 of 2014-01-03 
-Starting tweet 25 of 2014-01-02 
-Starting tweet 25 of 2014-01-01 
-Match!