v3 tagging done

master
mxmehl 8 years ago
parent cbbb664e04
commit e009060084

@ -1,224 +1,3 @@
c_errcode <- as.character(c_errors$code[r])
c_errissue <- as.character(c_errors$issue[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
c_errid <- as.character(c_errors$str_id[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
source("issuecomp-codingsample-function2.R")
}
c_tmp <- read.csv("issuecomp-codingsample-error1.csv", header = F, colClasses="character")
View(c_tmp)
View(c_errors)
View(c_tmp)
names(c_tmp) <- c("str_id", "all", "wrong", "tags", "text")
View(c_tmp)
c_tmp[, c("wrong", "tagged", "all", "text")]
View(c_tmp)
names(c_tmp) <- c("str_id", "all", "wrong", "tagged", "text")
c_tmp[, c("wrong", "tagged", "all", "text")]
c_error1 <- c_tmp[, c("wrong", "tagged", "all", "text")]
View(c_error1)
c_tmp <- read.csv("issuecomp-codingsample-error2.csv", header = F, colClasses="character")
View(c_tmp)
c_tmp <- read.csv("issuecomp-codingsample-error2.csv", header = F, colClasses="character")
names(c_tmp) <- c("str_id", "all", "missing", "tagged", "text")
c_error1 <- c_tmp[, c("missing", "tagged", "all", "text")]
c_error2 <- c_tmp[, c("missing", "tagged", "all", "text")]
View(c_error2)
c_error2 <- c_tmp[, c("missing", "text", "tagged", "all")]
View(c_error2)
View(c_error1)
View(c_error2)
c_tmp <- read.csv("issuecomp-codingsample-correct.csv", header = F, colClasses="character")
View(c_tmp)
names(c_tmp) <- c("str_id", "status", "issue", "tags", "text")
View(c_tmp)
c_currect <- c_tmp
c_correct <- c_tmp
rm(c_currect)
View(c_correct)
source("issuecomp-codingsample-function.R")
rm(c_err, c_result, c_samid, c_samno,c_samtags,c_samissue,c_samtext,c_yn)
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character", quote = "")
View(c_errors)
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
test <- "Zitat "total dämlich!""
tweets$id_str == "523512815425175552"
tweets[tweets$id_str == "523512815425175552"]
tweets[tweets$id_str == "523512815425175552", ]
tweets[tweets$id_str == "523512815425175552", "text"]
test <- tweets[tweets$id_str == "523512815425175552", "text"]
test
test <- c_tweets[ctweets$id_str == "523512815425175552", "text"]
test <- c_tweets[c_tweets$id_str == "523512815425175552", "text"]
test
str_replace(test, "\\"", ")
str_replace(test, "\\"", "")
str_replace(test, "\"", "")
str_detect(test, "\"")
test <- as.character(c_tweets[c_tweets$id_str == "523512815425175552", "text"])
test
c_tweets <- read.csv("tweets.csv", colClasses="character")
for(r in 1:nrow(c_tweets)) {
curtext <- as.character(c_tweets$text[r])
if(str_detect(curtext, "\"") {
c_tweets$text[r] <- str_replace(curtext, "\"", "")
}
}
for(r in 1:nrow(c_tweets)) {
curtext <- as.character(c_tweets$text[r])
if(str_detect(curtext, "\"") {
c_tweets$text[r] <- str_replace(curtext, "\"", "")
} else {}
}
for(r in 1:nrow(c_tweets)) {
curtext <- as.character(c_tweets$text[r])
if(str_detect(curtext, "\"") {
c_tweets$text[r] <- str_replace(curtext, "\"", "")
} else {
}
}
for(r in 1:nrow(c_tweets)) {
curtext <- as.character(c_tweets$text[r])
if(str_detect(curtext, "\"")) {
c_tweets$text[r] <- str_replace(curtext, "\"", "")
}
}
test <- as.character(c_tweets[c_tweets$id_str == "523512815425175552", "text"])
test
View(c_tweets)
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
View(c_errors)
names(c_errors) <- c("str_id", "code", "issue", "tags", "text")
View(c_errors)
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errissue <- as.character(c_errors$issue[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
c_errid <- as.character(c_errors$str_id[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
source("issuecomp-codingsample-function2.R")
}
issueheads
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errissue <- as.character(c_errors$issue[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
c_errid <- as.character(c_errors$str_id[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
source("issuecomp-codingsample-function2.R")
}
# All tweets with WRONG ISSUES
c_tmp <- read.csv("issuecomp-codingsample-error1.csv", header = F, colClasses="character")
names(c_tmp) <- c("str_id", "all", "wrong", "tagged", "text")
c_error1 <- c_tmp[, c("wrong", "tagged", "all", "text")]
# All tweets with MISSING ISSUES
c_tmp <- read.csv("issuecomp-codingsample-error2.csv", header = F, colClasses="character")
names(c_tmp) <- c("str_id", "all", "missing", "tagged", "text")
c_error2 <- c_tmp[, c("missing", "text", "tagged", "all")]
# All CORRECT tweets
c_tmp <- read.csv("issuecomp-codingsample-correct.csv", header = F, colClasses="character")
names(c_tmp) <- c("str_id", "status", "issue", "tags", "text")
c_correct <- c_tmp
View(c_error1)
View(c_error2)
View(c_error1)
View(c_correct)
test <- VAR(issues_i[,2:22], p=1, type="none", exogen = issues_s[,2:3])
plot(irf(test, impulse = names(issues_s[2:11]), response = names(issues_i[2:22])))
test <- VAR(issues[,2:32], p=1, type="none")
plot(irf(test, impulse = names(issues_s[2:11]), response = names(issues_i[2:22])))
VARselect(issues[,2:32], lag.max=8, type="none")
VARselect(issues[,2:32], lag.max=8, type="both")
VARselect(issues[,2:32], lag.max=30, type="both")
VARselect(issues[,2:32], lag.max=15, type="both")
for(i in 1:20) { cat(i,"\n") Sys.sleep(10)}
for(i in 1:20) { cat(i,"\n")Sys.sleep(10)}
for(i in 1:20) { cat(i,"\n")Sys.sleep(10)}
for(i in 1:20) { cat(i,"\n")
Sys.sleep(10)}
list.dirs()
list.files()
rm(results)
setwd("matched-ids/")
results_files <- list.files()
results_files
results_files <- "all.csv"
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)
results <- results[!duplicated(results), ]
names(results) <- c("date", "id_str", "issue", "tags")
results <- results[order(results$id_str), ]
row.names(results) <- NULL
results[23381,]
results[53381,]
results[43253,]
for(r in 53371:nrow(results)) {
curdate <- as.character(results$date[r])
curid <- as.character(results$id_str[r])
curissue <- as.character(results$issue[r])
curtag <- as.character(results$tags[r])
cat("Sorting match", r, "of 53383 \n")
# Update issue counter (date and issue)
issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
# Update tweet dataframe (id, issue and tags)
oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ",")
oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ",")
}
issues[issueheads] <- 0
View(issues)
for(r in 1:nrow(results)) {
curdate <- as.character(results$date[r])
curid <- as.character(results$id_str[r])
curissue <- as.character(results$issue[r])
curtag <- as.character(results$tags[r])
cat("Sorting match", r, "of 53383 \n")
# Update issue counter (date and issue)
issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
# Update tweet dataframe (id, issue and tags)
oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ",")
oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ",")
}
require(lubridate)
require(XML)
require(ggplot2)
require(reshape2)
require(stringr)
require(foreach)
require(doParallel)
for(r in 1:nrow(results)) {
curdate <- as.character(results$date[r])
curid <- as.character(results$id_str[r])
curissue <- as.character(results$issue[r])
curtag <- as.character(results$tags[r])
cat("Sorting match", r, "of 53383 \n")
# Update issue counter (date and issue)
issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
# Update tweet dataframe (id, issue and tags)
oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ",")
oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ",")
}
results[119,]
results[120,]
load(file = "tweets_untagged.RData")
setwd("~/Dokumente/Uni/Aktuell/BA-Arbeit/uni-ba-issuecomp")
results_files <- "matched-ids/all.csv"
@ -510,3 +289,224 @@ rm(delrow, r, acc)
acc_df$row.names <- NULL
row.names(acc_df) <- NULL
View(acc_df)
View(c_tweets)
issueheads
length(issueheads)
issuelist
length(issuelist)
length(issuelist[*])
length(issuelist[[*]])
length(issuelist[1:43])
length(issuelist[1)
length(issuelist[1])
length(issuelist[2])
length(issuelist[[1]])
length(issuelist[[2]])
length(issuelist[[70]])
length(issuelist[[43]])
length(issuelist[[44]])
length(issuelist[[1:43]])
length(issuelist[[1-43]])
length(issuelist[[2]])
test <- 0
num <- 0
for(i in 1:length(issuelist)) {
j <- length(issuelist[[i]])
num <- num + j
rm(j)
}
num
drop_s <- which(str_detect(names(issues), "^s"))
drop_i <- which(str_detect(names(issues), "^i"))
issues_i <- issues[,-drop_s]
issues_s <- issues[,-drop_i]
require(stringr)
drop_s <- which(str_detect(names(issues), "^s"))
drop_i <- which(str_detect(names(issues), "^i"))
issues_i <- issues[,-drop_s]
issues_s <- issues[,-drop_i]
issues_i$total <- rowSums(issues_i[2:ncol(issues_i)])
issues_i$entropy <- 0
for(r in 1:nrow(issues_i)) {
curtotal <- as.numeric(issues_i$total[r])
curp <- 0
for(c in 2:ncol(issues_i)) {
curcount <- as.numeric(issues_i[r,c])
curp[c] <- curcount / curtotal
}
curp <- curp [2:length(curp)-2]
curdrop <- which(curp==0)
curp <- curp[-curdrop]
issues_i$entropy[r] <- sum(-1 * curp * log(curp))
}
issues_s$total <- rowSums(issues_s[2:ncol(issues_s)])
issues_s$entropy <- 0
for(r in 1:nrow(issues_s)) {
curtotal <- as.numeric(issues_s$total[r])
curp <- 0
for(c in 2:ncol(issues_s)) {
curcount <- as.numeric(issues_s[r,c])
curp[c] <- curcount / curtotal
}
curp <- curp [2:length(curp)-2]
curdrop <- which(curp==0)
curp <- curp[-curdrop]
issues_s$entropy[r] <- sum(-1 * curp * log(curp))
}
stats_total <- data.frame(date=drange)
stats_total$tpd <- 0
stats_total$ipd <- issues_i$total
stats_total$spd <- issues_s$total
# Total number of tweets per day over time
for(r in 1:length(drange)) {
stats_total$tpd[r] <- length(tweets[tweets[, "created_at"] == drange[r], "id_str"])
}
stats_melt <- melt(stats_total, id="date")
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
geom_line()+
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
g1
require(ggplot2)
stats_melt <- melt(stats_total, id="date")
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
geom_line()+
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
geom_line()+
geom_smooth(size=1,formula = y ~ x, method="lm", se=FALSE, color=1)
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
geom_line()+
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
g1
# Visuals for entropy in time series
stats_entropy <- data.frame(date=drange)
stats_entropy$entropy <- issues_i$entropy
stats_entropy <- melt(stats_entropy, id="date")
require(reshape2)
stats_melt <- melt(stats_total, id="date")
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
geom_line()+
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
g1
stats_entropy <- data.frame(date=drange)
stats_entropy$entropy <- issues_i$entropy
stats_entropy <- melt(stats_entropy, id="date")
g1 <- ggplot(data = stats_entropy, aes(x=date,y=value,colour=variable, group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
g1
g1 <- ggplot(data = stats_entropy, aes(x=date,y=value,colour=variable, group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="lm", se=FALSE, color=1)
g1
vIssues <- VAR(issues_ts[,2:44], p=1, type="both")
require(vars)
VARselect(issues_ts, lag.max = 8, type = "both")
vIssues <- VAR(issues_ts[,2:44], p=1, type="both")
VARselect(issues_ts, lag.max = 16, type = "both")
VARselect(issues_ts, lag.max = 4, type = "both")
VARselect(issues_ts, lag.max = 5, type = "both")
VARselect(issues_ts, lag.max = 6, type = "both")
VARselect(issues_ts, lag.max = 5, type = "both")
names(issues_ts)
issues_ts
issues_ts[2:44]
issues_ts <- as.ts(issues[,2:44])
issues_ts[1:1]
issues_ts[,1]
issues_ts[1,1]
issues_ts2,1]
issues_ts[2,1]
issues_ts <- as.ts(issues[,2:44])
VARselect(issues_ts, lag.max = 5, type = "both")
VARselect(issues_ts, lag.max = 8, type = "both")
VARselect(issues_ts, lag.max = 7, type = "both")
VARselect(issues_ts, lag.max = 5, type = "both")
vIssues <- VAR(issues_ts[,2:44], p=5, type="both")
vIssues <- VAR(issues_ts, p=5, type="both")
plot(irf(vIssues, impulse = names(issues_s[2:23]), response = names(issues_i[2:22])))
require(stringr)
require(XML)
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
names(c_errors) <- c("str_id", "code", "issue", "tags", "text")
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errissue <- as.character(c_errors$issue[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
c_errid <- as.character(c_errors$str_id[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
source("issuecomp-codingsample-function2.R")
}
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errissue <- as.character(c_errors$issue[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
c_errid <- as.character(c_errors$str_id[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
source("issuecomp-codingsample-function2.R")
}
issueheads
for(i in 1:length(issueheads)) {paste(issueheads[i])}
for(i in 1:length(issueheads)) {cat(issueheads[i], "\n")}
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errissue <- as.character(c_errors$issue[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
c_errid <- as.character(c_errors$str_id[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
source("issuecomp-codingsample-function2.R")
}
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errissue <- as.character(c_errors$issue[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
c_errid <- as.character(c_errors$str_id[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
source("issuecomp-codingsample-function2.R")
}
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
names(c_errors) <- c("str_id", "code", "issue", "tags", "text")
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errissue <- as.character(c_errors$issue[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
c_errid <- as.character(c_errors$str_id[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
source("issuecomp-codingsample-function2.R")
}
c_tmp <- read.csv("issuecomp-codingsample-error1.csv", header = F, colClasses="character")
names(c_tmp) <- c("str_id", "all", "wrong", "tagged", "text")
c_error1 <- c_tmp[, c("wrong", "tagged", "all", "text")]
c_tmp <- read.csv("issuecomp-codingsample-error2.csv", header = F, colClasses="character")
names(c_tmp) <- c("str_id", "all", "missing", "tagged", "text")
c_error2 <- c_tmp[, c("missing", "text", "tagged", "all")]
View(c_error2)
summary(ur.df(issues_ts[, 2], type ="none", lags=1))
require(vars)
summary(ur.df(issues_ts[, 2], type ="none", lags=1))
stability(vIssues)
stability(vIssues[2:])
stability(vIssues[2:44])
plot(stability(vIssues))
class(vIssues)
summary(vIssues)
plot(stability(vIssues[2]))
plot(stability(vIssues), nc=2)
plot(stability(vIssues), h=0.15)
stability(vIssues)
efp(formula = formula, data = data, type = type, h = h, dynamic = dynamic,
rescale = rescale)
plot(stability(vIssues), h=0.15)
plot(stability(vIssues, h=0.15))
plot(stability(vIssues, h=0.15, rescale = TRUE))
plot(stability(vIssues, h=0.15, rescale = TRUE), nc=2)
par("mar")
par(mar=c(1,1,1,1))
plot(stability(vIssues, h=0.15, rescale = TRUE), nc=2)

@ -147,9 +147,9 @@ stopCluster(cl)
# IMPORT RESULTS ----------------------------------------------------------
# Import all files which have been generated at the categorisation run above.
#setwd("matched-ids/")
#results_files <- list.files()
results_files <- "matched-ids/all.csv"
results_files <- list.files("matched-ids/", full.names = T)
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)
@ -172,13 +172,14 @@ row.names(results) <- NULL
# Reset issues counter
#issues[issueheads] <- 0
for(r in 33170:nrow(results)) {
nrow_results <- nrow(results)
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 53383 \n")
cat("Sorting match", r, "of", nrow_results, "\n")
# Update issue counter (date and issue)
issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1

@ -83,10 +83,11 @@ g1
# test <- VAR(issues_s[,2:11], p=1, type="none")
# VAR(issues_s[,2:23], p=1, type=c("const", "trend", "both", "none"), season=NULL, exogen = issues_i[2:22])
issues_ts <- as.ts(issues)
vIssues <- VAR(issues_ts[,2:44], p=1, type="both")
issues_ts <- as.ts(issues[,2:44])
VARselect(issues_ts, lag.max = 5, type = "both")
vIssues <- VAR(issues_ts, p=5, type="both")
plot(irf(test, impulse = names(issues_s[2:23]), response = names(issues_i[2:22])))
plot(irf(vIssues, impulse = names(issues_s[2:23]), response = names(issues_i[2:22])))
capture.output(print(summary(test), prmsd=TRUE, digits=1), file="out.txt")

@ -1,11 +1 @@
<s.ukraine>
<tag>#Janukowitsch</tag>
</s.ukraine>
<i2.civil>
<tag>Foltermethode</tag>
</i2.civil>
<i19.ib>
--<tag>Afghanistan</tag>
</i19.ib>

@ -46,6 +46,17 @@
</i1.macro>
<i2.civil>
<tag>Foltermethode</tag>
<tag>Immigrant</tag>
<tag>Menschengerichtshof</tag>
<tag>Einwander</tag>
<tag>Faschismus</tag>
<tag>Faschist</tag>
<tag>Antisemitismus</tag>
<tag>Antisemitist</tag>
<tag>Nationalismus</tag>
<tag>Nationalist</tag>
<tag>Flüchtlingspolitik</tag>
<tag>Migration</tag>
<tag>Migrant</tag>
<tag>Flüchtlingsstrom</tag>
@ -67,6 +78,7 @@
<tag>Rassismus</tag>
<tag>rassistisch</tag>
<tag>Rechtsextremismus</tag>
<tag>Nazi</tag>
<tag>Nazis</tag>
<tag>Wahlrecht</tag>
@ -397,6 +409,11 @@
</i6.edu>
<i7.env>
<tag>Energiestrategie</tag>
<tag>#EEG</tag>
<tag>bundnaturschutz</tag>
<tag>BUND</tag>
<tag>Klimakonferenz</tag>
<tag>Energiewende</tag>
<tag>Klimaschutz</tag>
<tag>Klimagipfel</tag>
@ -607,6 +624,8 @@
</i8.energy>
<i10.trans>
<tag>Deutsche Bahn</tag>
<tag>#GDL</tag>
<tag>LKWs</tag>
<tag>PKWs</tag>
@ -741,6 +760,12 @@
</i10.trans>
<i12.law>
<tag>Euthanasie</tag>
<tag>Familienarbeitszeit</tag>
<tag>Waffenarsenal</tag>
<tag>NSU</tag>
<tag>Crystal Meth</tag>
<tag>Ecstacy</tag>
<tag>Vorratsdatenspeicherung</tag>
<tag>VDS</tag>
<tag>Cybercrime</tag>
@ -904,15 +929,14 @@
<tag>Erdbeben</tag>
<tag>Frühwarnsystem</tag>
<!-- 1227 -->
<tag>Terrorismus</tag>
<tag>Personalausweis</tag>
<tag>Ausweis</tag>
<tag>Terrorist</tag>
<!-- 1299 -->
<tag>Opferentschädigung</tag>
</i12.law>
<i13.social>
<tag>Pflegezeit</tag>
<!-- 1300 -->
<tag>Sozialpolitik</tag>
<tag>Pflegeversicherung</tag>
@ -982,6 +1006,8 @@
</i13.social>
<i14.house>
<tag>preiswert Wohnen</tag>
<tag>preiswertes Wohnen</tag>
<!-- 1400 -->
<tag>Wohnungswesen</tag>
<tag>Raumungordnung</tag>
@ -1157,6 +1183,7 @@
<tag>Reiseversicherung</tag>
<!-- 1525 -->
<tag>Verbaucherschutz</tag>
<tag>Verbraucherinteressen</tag>
<tag>Verbaucherbetrug</tag>
<tag>Werbebetrug</tag>
<tag>Verbraucherschutzministerium</tag>
@ -1189,6 +1216,8 @@
<i16.defense>
<tag>Auschwitz</tag>
<tag>2 Weltkrieg</tag>
<tag>zweiter Weltkrieg</tag>
<tag>Rüstungsbudget</tag>
<tag>Rüstungsausgaben</tag>
@ -1352,6 +1381,7 @@
<i17.science>
<tag>Sicherheitslücke</tag>
<tag>Internetsteuer</tag>
<!-- 1700 -->
<tag>Weltraumforschung</tag>
@ -1494,9 +1524,12 @@
</i18.trade>
<i19.ib>
<tag>#EU</tag>
<tag>Ungarn</tag>
<tag>Außenpolitik</tag>
<tag>außenpolitisch</tag>
<tag>menschenrechtsbetont</tag>
<tag>Türkei</tag>
<!-- 1900 -->
<tag>internationale Beziehungen</tag>
@ -1619,7 +1652,6 @@
<tag>Japan</tag>
<tag>Südostasien</tag>
<tag>Indien</tag>
<tag>Afghanistan</tag>
<tag>China</tag>
<tag>chinesisch</tag>
<tag>Taiwan</tag>
@ -1644,7 +1676,6 @@
<tag>religiöse Verfolgung</tag>
<tag>Verbrechen gegen die Menschheit</tag>
<tag>Verbrechen gegen die Menschlichkeit</tag>
<tag>Folter</tag>
<tag>Kindersoldat</tag>
<tag>Menschenrechtskonvention</tag>
<!-- 1926 -->
@ -1824,6 +1855,8 @@
</s.nsa>
<s.is>
<tag>Islamischer Staat</tag>
<tag>Islamischen Staates</tag>
<tag>ISIS</tag>
<tag>IS</tag>
<tag>al Baghdadi</tag>
@ -1858,6 +1891,8 @@
<tag>Donetsk</tag>
<tag>Donezk</tag>
<tag>Euromaidan</tag>
<tag>#Maidan</tag>
<tag>#Janukowitsch</tag>
</s.ukraine>
<s.hk>
@ -1891,6 +1926,7 @@
</s.ferguson>
<s.boko>
<tag>200 entführte Mädchen</tag>
<tag>Boko Haram</tag>
</s.boko>
@ -1970,6 +2006,8 @@
<tag>Brasilien</tag>
<tag>#WorldCup</tag>
<tag>#WM2014</tag>
<tag>#GERALG</tag>
<tag>#ALGGER</tag>
</s.wm>
<s.sotschi>

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