diff --git a/.Rhistory b/.Rhistory
index e0e8af3..43ae5a0 100644
--- a/.Rhistory
+++ b/.Rhistory
@@ -1,93 +1,3 @@
-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
 require(lubridate)
 require(XML)
 require(ggplot2)
@@ -95,10 +5,19 @@ require(reshape2)
 require(stringr)
 library(foreach)
 library(doParallel)
-# MATCH TWEETS ------------------------------------------------------------
-id_folder <- "matched-ids"
-unlink(id_folder, recursive = TRUE)
-dir.create(id_folder)
+source("issuecomp-functions.R")
+getwd()
+setwd("~/Dokumente/Uni/Aktuell/BA-Arbeit/uni-ba-issuecomp")
+getwd()
+list.files()
+list.files("matched-ids/")
+load(file = "tweets_untagged.RData")
+issues <- data.frame(date = drange)
+# 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)
 issues <- data.frame(date = drange)
 issuelist <- readLines("issues.xml")
 issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
@@ -107,86 +26,148 @@ 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)
+list.files("matched-ids/")
+results <- list.files("matched-ids/")
+results
+read.csv("matched-ids/i10.trans.csv")
+read.csv("matched-ids/i10.trans.csv", sep=";")
+read.csv("matched-ids/i10.trans.csv", sep=";", stringsAsFactors=F)
+read.csv("matched-ids/i10.trans.csv", sep=";", stringsAsFactors=T)
+reesult_files <- read.csv("matched-ids/i10.trans.csv", sep=";", stringsAsFactors=F)
+View(reesult_files)
+result_files <- read.csv("matched-ids/i10.trans.csv", sep=";", colClasses=c("date", "character", "character", "character"))
+result_files <- read.csv("matched-ids/i10.trans.csv", sep=";", colClasses=c("character", "character", "character", "character"))
+rm(reesult_files)
+View(result_files)
+nrow(result_files)
+result_files <- result_files(!duplicated(result_files))
+result_files <- result_files[!duplicated(result_files)]
+result_files <- result_files[!duplicated(result_files), ]
+nrow(result_files)
+result_files <- read.csv("matched-ids/i10.trans.csv", sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+View(result_files)
+read.results
+results
+setwd("matched-ids/")
+list.files("")
+getwd()
+list.files()
+results <- list.files()
+results
+results_cat <- read.csv(results, sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+results_cat <- read.csv(results[1], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+results_cat
+View(results_cat)
+source("issuecomp-functions.R")
+setwd("~/Dokumente/Uni/Aktuell/BA-Arbeit/uni-ba-issuecomp")
+source("issuecomp-functions.R")
+insertRow
+results_temp <- read.csv(results[2], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+setwd("matched-ids/")
+results_temp <- read.csv(results[2], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+rm(result_files)
+insertRow(existingDF = results_cat, results_temp)
+rm(results_cat)
+for(r in 1:length(results)) {
+if(r == 1) {
+results_cat <- read.csv(results[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+} else {
+results_temp <- read.csv(results[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+insertRow(results_cat, results_temp)
+}
+}
+for(r in 1:length(results)) {
+if(r == 1) {
+results_cat <- read.csv(results[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+} else {
+results_temp <- read.csv(results[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+results_cat insertRow(results_cat, results_temp)
+}
+}
+for(r in 1:length(results)) {
+if(r == 1) {
+results_cat <- read.csv(results[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+} else {
+results_temp <- read.csv(results[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+results_cat <- insertRow(results_cat, results_temp)
+}
+}
+View(results_cat)
+results_cat[20000]
+results_cat[20000, ]
+rm(r, results_temp)
+results_cat <- results_cat[!duplicated(results_cat), ]
+View(results_cat)
+rm(results, results_cat)
+results_files <- list.files()
+for(r in 1:length(results)) {
+if(r == 1) {
+results <- read.csv(results_files[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+} else {
+results_temp <- read.csv(results_files[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+results <- insertRow(results_cat, results_temp)
+}
+}
+rm(r, results_temp)
+results <- results[!duplicated(results), ]
+results_files <- list.files()
+for(r in 1:length(results_files)) {
+if(r == 1) {
+results <- read.csv(results_files[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+} else {
+results_temp <- read.csv(results_files[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+results <- insertRow(results, results_temp)
+}
+}
+rm(r, results_temp)
+results <- results[!duplicated(results), ]
+View(results)
+View(issues)
+row.names(results) <- NULL
+View(results)
+rownames(results)
+row.names(results)
+names(results)
+View(tweets)
+View(tweets)
+names(results) <- c("date", "id_str", "issue", "tags")
+View(results)
+results_test <- results[order(results$id_str)]
+results_test <- results[order(results$id_str), ]
+View(results_test)
+results_files <- list.files()
+for(r in 1:length(results_files)) {
+if(r == 1) {
+results <- read.csv(results_files[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+} else {
+results_temp <- read.csv(results_files[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+results <- insertRow(results, results_temp)
+}
+}
+rm(r, results_temp)
+rm(r, results_temp, results_files)
+results <- results[!duplicated(results), ]
+names(results)
+names(results) <- c("date", "id_str", "issue", "tags")
+View(results)
+results_test <- results[order(results$id_str), ]
+row.names(results) <- NULL
+results <- results[order(results$id_str), ]
+row.names(results) <- NULL
+View(results)
+rm(results_test)
+View(issues)
+as.character(results$date[2])
+class(results$date)
+class(issues$date)
+View(issues)
+as.character(issues$date[2])
+issues$date[2]
+issuelist <- readLines("issues.xml")
+issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
+issuelist <- xmlToList(issuelist)
+issueheads <- names(issuelist)
 require(lubridate)
 require(XML)
 require(ggplot2)
@@ -194,319 +175,68 @@ require(reshape2)
 require(stringr)
 library(foreach)
 library(doParallel)
-drange[70]
-drange[80]
-drange[90]
-cl<-makeCluster(4)
-registerDoParallel(cl)
-foreach(d = 51:90, .packages = c("stringr"), .combine=rbind) %dopar% {
-#for(d in 1:nrow(issues)) {
-# Go through every day
-curdate <- issues$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
+issuelist <- readLines("issues.xml")
+issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
+issuelist <- xmlToList(issuelist)
+issueheads <- names(issuelist)
+setwd("~/Dokumente/Uni/Aktuell/BA-Arbeit/uni-ba-issuecomp")
+issuelist <- readLines("issues.xml")
+issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
+issuelist <- xmlToList(issuelist)
+issueheads <- names(issuelist)
+issues[issueheads] <- 0
+curdate <- as.character(results$date[3])
+curissue <- as.character(results$issue[3])
+curdate
+curissue
+issues[curdate, curissue] <- issues[curdate, curissue] + 1
+View(issues)
+issues <- data.frame(date = drange)
+issues[issueheads] <- 0
+View(issues)
+issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
+View(issues)
+for(r in 1:nrow(results)) {
+curdate <- as.character(results$date[r])
+curissue <- as.character(results$issue[r])
+issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
 }
-# 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])
+View(issues)
+issues[issueheads] <- 0
+View(issues)
+for(r in 1:nrow(results)) {
+curdate <- as.character(results$date[r])
+curid <- as.character(results$id_str[r])
+curissue <- as.character(results$issue[r])
+curtag <- as.character(results$tags[r])
+# Update issue counter (date and issue)
+issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
+# Update tweet dataframe (id, issue and tags)
+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, ",")
 }
+View(tweets)
+tweets$issue <- ""
+tweets$tags <- ""
+View(tweets)
+issues[issueheads] <- 0
+for(r in 1:nrow(results)) {
+curdate <- as.character(results$date[r])
+curid <- as.character(results$id_str[r])
+curissue <- as.character(results$issue[r])
+curtag <- as.character(results$tags[r])
+cat("Sorting match", r, "from", nrow(results), "\n")
+# Update issue counter (date and issue)
+issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
+# Update tweet dataframe (id, issue and tags)
+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, ",")
 }
-# 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
-require(lubridate)
-require(XML)
-require(ggplot2)
-require(reshape2)
-require(stringr)
-library(foreach)
-library(doParallel)
-cl<-makeCluster(3)
-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
-stopCluster(cl)
-drange[200]
-drange[300]
-drange[280]
-drange[270]
-drange[259]
+View(issues)
+View(tweets)
+View(tweets)
+save(tweets, file="tweets_tagged.RData")
diff --git a/issuecomp-analysis.R b/issuecomp-analysis.R
index 5f655c1..b19c48b 100644
--- a/issuecomp-analysis.R
+++ b/issuecomp-analysis.R
@@ -7,6 +7,7 @@ library(foreach)
 library(doParallel)
 
 source("issuecomp-functions.R")
+setwd("~/Dokumente/Uni/Aktuell/BA-Arbeit/uni-ba-issuecomp")
 
 
 load(file = "tweets_untagged.RData")
@@ -17,13 +18,8 @@ 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)
-
+# Import issues and prepare everything
+# Will only be filled after the large categorisation loop
 issues <- data.frame(date = drange)
 issuelist <- readLines("issues.xml")
 issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
@@ -33,15 +29,24 @@ issues[issueheads] <- 0
 tweets$issue <- ""
 tweets$tags <- ""
 
+
+# MATCH TWEETS ------------------------------------------------------------
+
+# Create folder where all results will be saved (saver for backup and import)
+id_folder <- "matched-ids"
+unlink(id_folder, recursive = TRUE)
+dir.create(id_folder)
+
+# Tag expansion for plural, genetiv etc
 tagexpand <- c("", "s", "n", "en", "er", "e")
 
-# Parallelisation
+# Parameters for parallelisation
 writeLines(c(""), "issuecomp-analysis.log")  
 cl<-makeCluster(4)
 registerDoParallel(cl)
 
-foreach(d = 260:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
-#for(d in 1:nrow(issues)) {
+# START CAT LOOP
+foreach(d = 1:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar% {
   # Go through every day
   curdate <- issues$date[d]
   cat(paste(as.character(curdate),"\n"), file="issuecomp-analysis.log", append=TRUE)
@@ -125,12 +130,58 @@ foreach(d = 260:nrow(issues), .packages = c("stringr"), .combine=rbind) %dopar%
 #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)
 
+
+
+# IMPORT RESULTS ----------------------------------------------------------
+
+# Import all files which have been generated at the categorisation run above.
+setwd("matched-ids/")
+results_files <- list.files()
+for(r in 1:length(results_files)) {
+  if(r == 1) {
+    results <- read.csv(results_files[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+  } else {
+    results_temp <- read.csv(results_files[r], sep=";", colClasses=c("character", "character", "character", "character"), header=F)
+    results <- insertRow(results, results_temp)
+  }
+}
+rm(r, results_temp, results_files)
+# Remove duplicates, sort chronologically
+results <- results[!duplicated(results), ]
+names(results) <- c("date", "id_str", "issue", "tags")
+results <- results[order(results$id_str), ]
+row.names(results) <- NULL
+
+
+# Now import all results in the dataframes "issues" and "tweets" 
+# (which wasn't possible in the categorisation process because of parallelisation)
+
+# Reset issues counter
+# issues[issueheads] <- 0
+
+for(r in 1:nrow(results)) {
+  curdate <- as.character(results$date[r])
+  curid <- as.character(results$id_str[r])
+  curissue <- as.character(results$issue[r])
+  curtag <- as.character(results$tags[r])
+  
+  cat("Sorting match", r, "of 62827 \n")
+  
+  # Update issue counter (date and issue)
+  issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
+  
+  # Update tweet dataframe (id, issue and tags)
+  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, ",")
+}
+
+
+
 # SAVING ------------------------------------------------------------------
 
-
-row.names(tweets) <- NULL
-write.csv(tweets, "tweets.csv")
-save(tweets, file="tweets.RData")
+save(tweets, file="tweets_tagged.RData")
 
 
 
diff --git a/tweets_tagged.RData b/tweets_tagged.RData
new file mode 100644
index 0000000..a67d9bb
Binary files /dev/null and b/tweets_tagged.RData differ