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mxmehl
2015-01-18 22:46:54 +01:00
parent ba40416197
commit 24f5b02221
6 changed files with 431 additions and 394 deletions
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@@ -1,389 +1,3 @@
source("issuecomp-codingsample-function2.R")
}
if(c_errcode == "1") {
#cat("Which issue is incorrect?\n")
repeat {
c_tag <- readYN("Which issue is incorrect?: ")
c_tag <- unlist(str_split(c_tag, ";"))
for(i in 1:length(c_tag)) {
if(checkIssue(c_tag[i], c_issueheads)) {status[i] <- TRUE} else {cat("Issue",c_tag[i],"does not exist. Please try again.\n")}
}
if(all(status)) {
break
}
}
if(c_errcode == "1") {
#cat("Which issue is incorrect?\n")
repeat {
c_tag <- readYN("Which issue is incorrect?: ")
c_tag <- unlist(str_split(c_tag, ";"))
for(i in 1:length(c_tag)) {
if(checkIssue(c_tag[i], c_issueheads)) {status[i] <- TRUE} else {cat("Issue",c_tag[i],"does not exist. Please try again.\n")}
}
if(all(status)) {
break
}
}
}
wdq
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errtags, "\n", sep="")
source("issuecomp-codingsample-function2.R")
}
source("issuecomp-codingsample-function2.R")
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errtags, "\n", sep="")
source("issuecomp-codingsample-function2.R")
}
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errtags, "\n", sep="")
source("issuecomp-codingsample-function2.R")
}
checkAllIssues <- function(string, issuelist) {
string <- unlist(str_split(string, ";"))
for(i in 1:length(string)) {
if(checkIssue(string[i], issuelist)) {
status[i] <- TRUE
}
else {
cat("Issue",string[i],"does not exist. Please try again.\n")
status[i] <- FALSE
}
}
}
test
checkAllIssues <- function(string, issuelist) {
string <- unlist(str_split(string, ";"))
for(i in 1:length(string)) {
if(checkIssue(string[i], issuelist)) {
status[i] <- TRUE
}
else {
cat("Issue",string[i],"does not exist. Please try again.\n")
status[i] <- FALSE
}
}
return(status)
}
test <- "issue.edathy"
checkAllIssues(test, c_issueheads)
test <- "issue.edathy"
checkAllIssues(test, c_issueheads)
rm(status)
checkAllIssues(test, c_issueheads)
checkAllIssues <- function(string, issuelist) {
status <- NULL
string <- unlist(str_split(string, ";"))
for(i in 1:length(string)) {
if(checkIssue(string[i], issuelist)) {
status[i] <- TRUE
}
else {
cat("Issue",string[i],"does not exist. Please try again.\n")
status[i] <- FALSE
}
}
return(status)
}
checkAllIssues(test, c_issueheads)
checkAllIssues("wdjqaowd", c_issueheads)
test <- checkAllIssues("wdjqaowd", c_issueheads)
test
test <- checkAllIssues("wdjqaow;wiqud", c_issueheads)
test
test <- checkAllIssues("wdjqaow;issue.edathy", c_issueheads)
test
checkAllIssues <- function(string, issuelist) {
status <- NULL
string <- unlist(str_split(string, ";"))
for(i in 1:length(string)) {
if(checkIssue(string[i], issuelist)) {
status[i] <- TRUE
}
else {
cat("Issue",string[i],"does not exist. Please try again.\n")
status[i] <- FALSE
}
}
return(status)
}
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errtags, "\n", sep="")
source("issuecomp-codingsample-function2.R")
}
checkAllIssues <- function(string, issuelist) {
status <- NULL
for(i in 1:length(string)) {
if(checkIssue(string[i], issuelist)) {
status[i] <- TRUE
}
else {
cat("Issue",string[i],"does not exist. Please try again.\n")
status[i] <- FALSE
}
}
return(status)
}
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errtags, "\n", sep="")
source("issuecomp-codingsample-function2.R")
}
for(r in 1:nrow(c_errors)) {
c_errcode <- as.character(c_errors$code[r])
c_errtags <- as.character(c_errors$tags[r])
c_errtext <- as.character(c_errors$text[r])
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errtags, "\n", sep="")
source("issuecomp-codingsample-function2.R")
}
View(c_issues)
View(tweets)
tweets$tagged <- NULL
View(c_tweets)
View(tweets)
# MATCH TWEETS ------------------------------------------------------------
id_folder <- "matched-ids"
unlink(id_folder, recursive = TRUE)
dir.create(id_folder)
issues <- data.frame(date = drange)
issuelist <- xmlToList("issues.xml")
issueheads <- names(issuelist)
issues[issueheads] <- 0
tweets$issue <- ""
tweets$tags <- ""
for(d in 1:nrow(issues)) {
# Go through every day
curdate <- issues$date[d]
cat(as.character(curdate),"\n")
# Put all tweets from specific day in a temporary DF
tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
for(t in 1:nrow(tweets_curday)){
# Select tweet's text, make it lowercase and remove hashtag indicators (#)
curtext <- as.character(tweets_curday$text[t])
curtext <- str_replace_all(curtext, "#", "")
curtext <- str_replace_all(curtext, "$", " ")
curtext <- str_replace_all(curtext, "http://.+?\\s", "URL ")
curid <- as.character(tweets_curday$id_str[t])
# Now test each single issue (not tag!)
for(i in 1:length(issuelist)) {
curtags <- as.character(issuelist[[i]])
curissue <- names(issuelist)[i]
curfile <- str_c(id_folder,"/",curissue,".csv")
# Now test all tags of a single issue
for(s in 1:length(curtags)) {
curtag <- curtags[s]
curchars <- nchar(curtag, type = "chars")
# Check if tag is an acronym. If so, ignore.case will be deactivated in smartPatternMatch
if(curchars <= 4) {
curacro <- checkAcronym(string = curtag, chars = curchars)
} else {
curacro <- FALSE
}
# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow 2 (Levenshtein distance)
tags_found <- smartPatternMatch(curtext, curtag, curchars, curacro)
if(tags_found == 1) {
# Raise number of findings on this day for this issue by 1
issues[d,curissue] <- issues[d,curissue] + 1
# Add issue and first matched tag of tweet to tweets-DF
oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
# Add information to file for function viewPatternMatching
write(str_c(curdate,";\"",curid,"\";",curtag), curfile, append = TRUE)
break
}
else {
#cat("Nothing found\n")
}
} # /for curtags
} # /for issuelist
} # /for tweets_curday
} # /for drange
date_start <- as.Date("2014-01-01")
date_end <- as.Date("2014-12-31")
drange <- as.integer(date_end - date_start)
drange <- date_start + days(0:drange)
# MATCH TWEETS ------------------------------------------------------------
id_folder <- "matched-ids"
unlink(id_folder, recursive = TRUE)
dir.create(id_folder)
issues <- data.frame(date = drange)
issuelist <- xmlToList("issues.xml")
issueheads <- names(issuelist)
issues[issueheads] <- 0
tweets$issue <- ""
tweets$tags <- ""
for(d in 1:nrow(issues)) {
# Go through every day
curdate <- issues$date[d]
cat(as.character(curdate),"\n")
# Put all tweets from specific day in a temporary DF
tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
for(t in 1:nrow(tweets_curday)){
# Select tweet's text, make it lowercase and remove hashtag indicators (#)
curtext <- as.character(tweets_curday$text[t])
curtext <- str_replace_all(curtext, "#", "")
curtext <- str_replace_all(curtext, "$", " ")
curtext <- str_replace_all(curtext, "http://.+?\\s", "URL ")
curid <- as.character(tweets_curday$id_str[t])
# Now test each single issue (not tag!)
for(i in 1:length(issuelist)) {
curtags <- as.character(issuelist[[i]])
curissue <- names(issuelist)[i]
curfile <- str_c(id_folder,"/",curissue,".csv")
# Now test all tags of a single issue
for(s in 1:length(curtags)) {
curtag <- curtags[s]
curchars <- nchar(curtag, type = "chars")
# Check if tag is an acronym. If so, ignore.case will be deactivated in smartPatternMatch
if(curchars <= 4) {
curacro <- checkAcronym(string = curtag, chars = curchars)
} else {
curacro <- FALSE
}
# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow 2 (Levenshtein distance)
tags_found <- smartPatternMatch(curtext, curtag, curchars, curacro)
if(tags_found == 1) {
# Raise number of findings on this day for this issue by 1
issues[d,curissue] <- issues[d,curissue] + 1
# Add issue and first matched tag of tweet to tweets-DF
oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
# Add information to file for function viewPatternMatching
write(str_c(curdate,";\"",curid,"\";",curtag), curfile, append = TRUE)
break
}
else {
#cat("Nothing found\n")
}
} # /for curtags
} # /for issuelist
} # /for tweets_curday
} # /for drange
View(tweets)
View(tweets)
# MATCH TWEETS ------------------------------------------------------------
id_folder <- "matched-ids"
unlink(id_folder, recursive = TRUE)
dir.create(id_folder)
issues <- data.frame(date = drange)
issuelist <- xmlToList("issues.xml")
issueheads <- names(issuelist)
issues[issueheads] <- 0
tweets$issue <- ""
tweets$tags <- ""
for(d in 1:nrow(issues)) {
# Go through every day
curdate <- issues$date[d]
cat(as.character(curdate),"\n")
# Put all tweets from specific day in a temporary DF
tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
for(t in 1:nrow(tweets_curday)){
# Select tweet's text, make it lowercase and remove hashtag indicators (#)
curtext <- as.character(tweets_curday$text[t])
curtext <- str_replace_all(curtext, "#", "")
curtext <- str_replace_all(curtext, "$", " ")
curtext <- str_replace_all(curtext, "http://.+?\\s", "URL ")
curid <- as.character(tweets_curday$id_str[t])
# Now test each single issue (not tag!)
for(i in 1:length(issuelist)) {
curtags <- as.character(issuelist[[i]])
curissue <- names(issuelist)[i]
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
}
# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow 2 (Levenshtein distance)
tags_found <- smartPatternMatch(curtext, curtag, curchars, curacro)
if(tags_found == 1) {
# 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)
break
}
else {
#cat("Nothing found\n")
}
} # /for curtags
} # /for issuelist
} # /for tweets_curday
} # /for drange
View(tweets)
View(c_errors)
View(tweets)
readYN <- function(question) {
n <- readline(prompt=question)
n <- as.character(n)
return(n)
}
checkIssue <- function(string, issuelist) {
status <- any(str_detect(string, issuelist))
return(status)
}
checkAllIssues <- function(string, issuelist) {
status <- NULL
for(i in 1:length(string)) {
if(checkIssue(string[i], issuelist)) {
status[i] <- TRUE
}
else {
cat("Issue",string[i],"does not exist. Please try again.\n")
status[i] <- FALSE
}
}
return(status)
}
View(tweets)
View(tweets)
write.csv(tweets, "tweets.csv")
save(tweets, file="tweets.RData")
write.csv(tweets, "tweets.csv")
save(tweets, file="tweets.RData")
c_tweets <- read.csv("tweets.csv")
View(c_tweets)
c_tweets$X <- NULL
# Read all issues from XML file
c_issues <- data.frame(date = drange)
c_issuelist <- xmlToList("issues.xml")
c_issueheads <- names(issuelist)
c_issues[issueheads] <- 0
source("issuecomp-codingsample-function.R")
rm(c_err, c_result, c_samid, c_samno,c_samtags,c_samissue,c_samtext,c_yn)
rm(c_samtag)
rm(tweets_curday,curacro, curchars, curdate,curfile,curid,curissue,curtag,curtags,curtext,d,date_end,date_start,drange,i,id_folder,oldissue,oldtag,s,t,tags_found)
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$code[r])
@@ -510,3 +124,389 @@ acc_df <- acc_df[-delrow, ]
rm(delrow, r, acc)
acc_df$row.names <- NULL
row.names(acc_df) <- NULL
require(lubridate)
require(XML)
require(ggplot2)
require(reshape2)
require(stringr)
source("issuecomp-functions.R")
load("tweets.RData")
View(tweets)
View(tweets)
View(tweets)
date_start <- as.Date("2014-01-01")
date_start + days
date_start + days(1)
date_start + days(0)
date_start + days(0:2)
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)
curdate <- date_start + days(2)
curdate
tweets[tweets[, "created_at"] == curdate, "msg_id"]
View(tweets)
curdate
tweets[tweets[, "created_at"] == "2014-01-01", "msg_id"]
tweets[tweets[, "created_at"] == curdate, "id_str"]
drange
length(tweets[tweets[, "created_at"] == curdate, "id_str"])
length(tweets[tweets[, "created_at"] == curdate+1, "id_str"])
length(tweets[tweets[, "created_at"] == curdate+15, "id_str"])
stats <- data.frame(x=NULL)
View(stats)
stats <- data.frame(date=drange)
View(stats)
stats$tpd <- NULL
stats$tpd <- ""
stats$tpd <- NULL
stats$tpd[1] <- 2
View(stats)
stats$tpd[2] <- 3
View(stats)
stats$tpd <- ""
stats$tpd <- NULL
stats$tpd <- ""
stats$tpd[1] <- 2
View(tweets)
View(stats)
stats <- data.frame(date=drange)
stats$tpd <- ""
# Total number of tweets per day over time
for(r in 1:length(drange)) {
stats$tpd[r] <- length(tweets[tweets[, "created_at"] == curdate, "id_str"])
}
View(stats)
drange[2]
stats <- data.frame(date=drange)
stats$tpd <- ""
# Total number of tweets per day over time
for(r in 1:length(drange)) {
stats$tpd[r] <- length(tweets[tweets[, "created_at"] == drange[r], "id_str"])
}
View(stats)
plot.ts(x = stats$tpd, y=stats$date)
plot.ts(x = stats$date, y=stats$tpd)
g1 <- ggplot(stats, aes(date,tpd))
g1 <- g1 + geom_histogram(fill="steelblue", stat="identity")
g1 <- g1 + stat_smooth(size=1,colour="red",method="loess", se=FALSE)
g1 <- gg1 + ggtitle("Zeitliche Entwicklung von plötzlichen Medienfokussen") + xlab("Einzelne Monate") + ylab("Plötzliche Medienfokusse")
g1
g1 <- ggplot(stats, aes(date,tpd))
g1 <- g1 + geom_histogram(fill="steelblue", stat="identity")
g1
g1 <- g1 + stat_smooth(size=1,colour="red",method="loess", se=FALSE)
g1
g1 <- ggplot(stats, aes(date,tpd))
g1 <- g1 + geom_line()
g1
g1 <- ggplot() + geom_line(data = stats, aes(x=date,y=tpd, color=black))
g1
g1 <- ggplot() + geom_line(data = stats, aes(x=date,y=tpd, color="black"))
g1
g1 <- ggplot() + geom_line(data = stats, aes(x=date,y=tpd))
g1
ggplot(stats, aes(date, tpd)) + geom_line() +
scale_x_date(format = "%b-%Y") + xlab("") + ylab("Daily Views")
ggplot(stats, aes(date, tpd)) + geom_line() +
scale_x_date() + xlab("") + ylab("Daily Views")
lapply(stats, class)
stats$tpd <- 0
lapply(stats, class)
stats <- data.frame(date=drange)
stats$tpd <- 0
# Total number of tweets per day over time
for(r in 1:length(drange)) {
stats$tpd[r] <- length(tweets[tweets[, "created_at"] == drange[r], "id_str"])
}
View(stats)
plot.ts(x = stats$date, y=stats$tpd)
g1 <- ggplot() + geom_line(data = stats, aes(x=date,y=tpd))
g1
ggplot(stats, aes(date, tpd)) + geom_line() +
scale_x_date() + xlab("") + ylab("Daily Views")
g1 <- ggplot() +
geom_line(data = stats, aes(x=date,y=tpd)) +
stats_smooth(size=1,colour="red",method="loess", se=FALSE)
g1
g1 <- ggplot() +
geom_line(data = stats, aes(x=date,y=tpd)) +
stat_smooth(size=1,colour="red",method="loess", se=FALSE)
g1
g1 <- ggplot() +
geom_line(data = stats, aes(x=date,y=tpd)) +
stat_smooth(colour="red",method="loess", se=FALSE)
g1
g1 <- ggplot() +
geom_line(data = stats, aes(x=date,y=tpd)) +
stat_smooth(colour="red",method="lm", se=FALSE)
g1
g1 <- ggplot() +
geom_line(data = stats, aes(x=date,y=tpd)) +
geom_smooth(colour="red",method="lm", se=FALSE)
g1
g1 <- ggplot() +
geom_line(data = stats, aes(x=date,y=tpd)) +
geom_smooth(colour="red",method="loess", se=FALSE)
g1
g1 <- ggplot() +
geom_line(data = stats, aes(x=date,y=tpd)) +
geom_smooth(size=1,colour="red",method="loess", se=FALSE)
g1
g1 <- g1 + geom_smooth(size=1,colour="red", method="loess", se=FALSE)
g1
g1 <- ggplot() + geom_line(data = stats, aes(x=date,y=tpd))
g1 <- g1 + geom_smooth(size=1,colour="red", method="loess", se=FALSE)
g1
g1 <- ggplot() + geom_line(data = stats, aes(x=date,y=tpd))
g1
g1 + geom_smooth()
g1 + geom_smqwd
g1 <- ggplot() + geom_point(data = stats, aes(x=date,y=tpd))
g1
g1 <- g1 + geom_smooth(size=1,colour="red", method="loess", se=FALSE)
g1
g1 <- ggplot() + geom_point(data = stats, aes(x=date,y=tpd))
g1 <- g1 + geom_smooth(size=1,method="loess", se=FALSE)
g1
g1 <- ggplot() + geom_point(data = stats, aes(x=date,y=tpd))
g1 <- g1 + geom_smooth(size=1,method="loess", se=FALSE, aes(group=1))
g1
g1 <- ggplot() + geom_point(data = stats, aes(x=date,y=tpd)) +
geom_smooth(size=1,method="loess", se=FALSE, aes(group=1))
g1
g1 <- ggplot() + geom_point(data = stats, aes(x=date,y=tpd)) +
geom_smooth(size=1,method="loess", se=FALSE, aes(x = date, y=tpd))
g1
geom_smooth(size=1,method="loess", se=FALSE)
g1 <- ggplot() + geom_point(data = stats, aes(x=date,y=tpd)) +
geom_smooth(size=1,method="loess", se=FALSE)
g1
plot.ts(x = stats$date, y=stats$tpd)
g1 <- ggplot() + geom_point(data = stats, aes(x=date,y=tpd, color=group)) +
geom_smooth(size=1,method="loess", se=FALSE)
g1
install.packages(c("BH", "bibtex", "devtools", "dplyr", "httr", "jsonlite", "lazyeval", "manipulate", "RCurl", "ROAuth", "rstudioapi", "sp", "stringi"))
g1 <- ggplot(data = stats, aes(x=date,y=tpd, color=variable, group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE)
g1
stats_melt <- melt(stats, id="date")
View(stats_melt)
View(stats_melt)
stats_melt <- melt(stats, id="date")
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,color=variable, group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE)
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,color=1, group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE)
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,color=1, group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, colors="red")
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,color=1, group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color="red")
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,color="black", group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color="red")
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,color="yellow", group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color="red")
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour="black", group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color="red")
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour="#FFFFFF", group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color="red")
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour="vqwdqw", group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color="red")
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="red")
g1
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=1, group=variable)) +
geom_line() +
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color="red")
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
require(lubridate)
require(XML)
require(ggplot2)
require(reshape2)
require(stringr)
source("issuecomp-functions.R")
rm(curdate)
rm(date_end, date_start)
rm(g1, r, )
rm(g1, r)
id_folder <- "matched-ids"
unlink(id_folder, recursive = TRUE)
dir.create(id_folder)
issues <- data.frame(date = drange)
View(issues)
issuelist <- xmlToList("issues.xml")
issuelist
issueheads <- names(issuelist)
issueheads
issues[issueheads] <- 0
tweets$issue <- ""
tweets$tags <- ""
View(issues)
# MATCH TWEETS ------------------------------------------------------------
id_folder <- "matched-ids"
unlink(id_folder, recursive = TRUE)
dir.create(id_folder)
issues <- data.frame(date = drange)
issuelist <- xmlToList("issues.xml")
issueheads <- names(issuelist)
issues[issueheads] <- 0
tweets$issue <- ""
tweets$tags <- ""
for(d in 1:nrow(issues)) {
# Go through every day
curdate <- issues$date[d]
cat(as.character(curdate),"\n")
# Put all tweets from specific day in a temporary DF
tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
for(t in 1:nrow(tweets_curday)){
# Select tweet's text, make it lowercase and remove hashtag indicators (#)
curtext <- as.character(tweets_curday$text[t])
curtext <- str_replace_all(curtext, "#", "")
curid <- as.character(tweets_curday$id_str[t])
# Now test each single issue (not tag!)
for(i in 1:length(issuelist)) {
curtags <- as.character(issuelist[[i]])
curissue <- names(issuelist)[i]
curfile <- str_c(id_folder,"/",curissue,".csv")
# Now test all tags of a single issue
for(s in 1:length(curtags)) {
curtag <- curtags[s]
curchars <- nchar(curtag, type = "chars")
# Check if tag is an acronym. If so, ignore.case will be deactivated in smartPatternMatch
if(curchars <= 4) {
curacro <- checkAcronym(string = curtag, chars = curchars)
} else {
curacro <- FALSE
}
# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow 2 (Levenshtein distance)
tags_found <- smartPatternMatch(curtext, curtag, curchars, curacro)
if(tags_found == 1) {
# Raise number of findings on this day for this issue by 1
issues[d,curissue] <- issues[d,curissue] + 1
# Add issue and first matched tag of tweet to tweets-DF
oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ";")
oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ";")
# Add information to file for function viewPatternMatching
write(str_c(curdate,";\"",curid,"\";",curtag), curfile, append = TRUE)
break
}
else {
#cat("Nothing found\n")
}
} # /for curtags
} # /for issuelist
} # /for tweets_curday
} # /for drange
View(issues)
# MATCH TWEETS ------------------------------------------------------------
id_folder <- "matched-ids"
unlink(id_folder, recursive = TRUE)
dir.create(id_folder)
issues <- data.frame(date = drange)
issuelist <- xmlToList("issues.xml")
issueheads <- names(issuelist)
issues[issueheads] <- 0
tweets$issue <- ""
tweets$tags <- ""
for(d in 1:nrow(issues)) {
# Go through every day
curdate <- issues$date[d]
cat(as.character(curdate),"\n")
# Put all tweets from specific day in a temporary DF
tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
for(t in 1:nrow(tweets_curday)){
# 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(issuelist)) {
curtags <- as.character(issuelist[[i]])
curissue <- names(issuelist)[i]
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
}
# Match current tweet with tag. If >= 5 letters allow 1 changed letter, if >=8 letters allow 2 (Levenshtein distance)
tags_found <- smartPatternMatch(curtext, curtag, curchars, curacro)
if(tags_found == 1) {
# 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)
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)
View(issues)
save(issues, "issues.RData")
save(issues, file="issues.RData")
readYN <- function(question) {
n <- readline(prompt=question)
n <- as.character(n)
return(n)
}
checkIssue <- function(string, issuelist) {
status <- any(str_detect(string, issuelist))
return(status)
}
checkAllIssues <- function(string, issuelist) {
status <- NULL
for(i in 1:length(string)) {
if(checkIssue(string[i], issuelist)) {
status[i] <- TRUE
}
else {
cat("Issue",string[i],"does not exist. Please try again.\n")
status[i] <- FALSE
}
}
return(status)
}
require(stringr)
require(XML)
issuecomp-codingsample-correct.csv
+29
View File
@@ -1,2 +1,31 @@
"443032724505624576",0,"","","RT @Linksfraktion: Sevim Dagdelen: Optionspflicht abschaffen – ohne „Wenn“ und „Aber“ http://t.co/PXVz60RyDa"
"464039981766684672",0,"","","Hange spricht von einer Kutsche ohne Dach in der wir fahren und hoffen, dass es nicht regne #btADA"
"528513118440525824",0,"","","Dora zu Erfolgen der #Hamburger Linken: kostenfreies Mittag + Initiative, dass Maklergebühr nicht von Vermieter*innen.bezahlt werden müssen "
"511144502590181376",0,"","","RT @2kdei: TY! RİP @SajadJiyad: post about David Haines? Use this photo. He would want us to remember him. URL #ISISmedi… "
"515791668969504768",0,"","","Anschauen: Beitrag Heute Show zu #TTIP URL "
"533717720689549312",0,"","","RT @JUKoMo: "Wie groß muss die Angst der SPD vor Julia Klöckner sein?" Starker @LSaktuellRP-Kommentar zum SPD-Parteitag: URL "
"472393996879527936",0,"","","RT @johannisbear: Bitte RT! Bitte helft @ulf_der_freak #Aurela darf nicht sterben! URL "
"499494814778662912",0,"","","Das wievielte Mal verspricht #Merkel die Angleichung der #Ostrenten an Westniveau? Es gibt gute Gründe zu misstrauen URL "
"530750832443400192",0,"","","ist - gezwungenermaßen - mit dem #Fernbus unterwegs #gdlstreik "
"532310093904089088",0,"","","SPD will Waldschluchtpfad als Dauerstandort - Nachrichten Gatow | SPANDAUER VOLKSBLATT URL "
"465407100408320000",0,"","","Die neue Modernität in den Kleingarten Kneipen URL "
"428481075732811776",0,"civil.208;","Datenschutz;",""Datenschutz soll nicht unverhältnismäßig geschwächt werden." Was heißt da unverhältnismäßig? #Regierungserklärung #Merkel #Bundestag "
"421711548189786114",0,"","","...und inzwischen gute Freunde. URL "
"532608281009979392",0,"","","RT @initiatived21: “@anipenny: ”Graswurzelbewegg medienpägogisch interessierter Lehrer vernetzt sich, braucht aber auch Unterstützg“ @Esken… "
"537931613464965121",0,"","","RT @StefanKaufmann: Es läuft Plenardebatte zum Haushalt des Bundesmin. für Bild. und Forschung. Trotz Schwarzer Null steigt Etat deutlich -… "
"499843193069129728",0,"","","#CETA - der komplette Text wurde heute geleakt: https://t.co/YeWUsSAHoB "
"477758769703944194",0,"","","Beim Tag der Offenen Tür des THW beeindruckt von der Vielfalt der Einsätze der Organisation. 10 Mill. im Haushalt sind hier gut eingesetzt "
"539467838520832000",0,"","","RT @spdbt: KoA-Vertrag muss gelten! @ThomasOppermann: „Bei #Maut darf es keine Mehrbelastung für deutsche Autofahrer geben." URL "
"449534756259381248",0,"","","Höflich, aber klares Statement zu Menschenrechten. Der Bundespräsident macht das gut! #China #XiJinping URL "
"514314498510168065",0,"","","RT @zeitonline_wir: Ban Ki Moon lädt zum #Klimagipfel. 120 Staats- und Regierungschefs kommen. Nur nicht Angela Merkel. (ae) #climate2014 h… "
"434413898054524928",0,"","","RT @KonstantinNotz: Zum Appell der SchriftstellerInnen URL und Videobericht zum Empfang der #grünen Bundestagsfraktion h… "
"509707990929534976",0,"","","RT @weltnetzTV: URL in Kooperation mit theREALnews! URL "
"542066419274637312",0,"","","RT @tagesthemen: "Ein bescheuerter Satz" - Sigmund Gottlieb kommentiert #YallaCSU. Jetzt in den Tagesthemen. URL "
"508921157131984896",0,"","","RT @drthomasfeist: #gain2014 @MartinRabanus @KaiGehring @PLengsfeld @KarambaDiaby @the_dfg @DAADnewyork @AvHStiftung @UniLeipzig URL "
"540745511024992257",0,"","","RT @maybritillner: .@MikeMohring Der Freistaat #Thueringen hat es nicht verdient von einer Regierung geführt zu werden, die sich als Experi… "
"507492334347763712",0,"","","Bitte RT: Wer kann helfen? Brauchen ganz dringend mobile Duschcontainer für die Flüchtlingszelte in #Nürnberg #followerpower "
"485509000268902400",0,"","","#WM2014 #Deutschland #GER - #Thalheim #Erzgebirge URL "
"542710860528234497",0,"","","Illegaler #Kunsthandel blüht! BReg muss nachbessern. Kein Umschlagplatz BRD f. Raubkunst. Dazu @GreenClaudia + ich: https://t.co/tr16CjQl42 "
"535525766919106560",0,"","","RT @EU_Salon: .@DJanecek: #TTIP Zivilgesellsxhaft hat Funktion zu treiben... ohne kritische Masse hätte es Diskussion so nicht gegeben. #ES3 "
"472481188641124352",0,"","","Vor dem Grand Serail in Beirut,- im Schatten @nouripour :-) URL "
"532818411374788608",0,"","","Laut einer Studie treibt unsere Debatte um Mietpreisbremse Mieten in die Höhe - tolle Wurst! "
Can't render this file because it contains an unexpected character in line 6 and column 43.
issuecomp-codingsample-error.csv
+3
View File
@@ -1,3 +1,6 @@
"532463690013233152",1,"","","RT @cordhos: ! “@cducsubt: Paul Breitner vom @FCBayern - #Bundestag jetzt mit eigenem Fanclub @hahnflo @DoroBaer @dieAlbsteigerin http://t.…"
"516584367448403968",1,"","","Debate und critics in the parlamentarian assembly of the European Council about the elections in #Turkey @PACE_News @GeziParkii"
"516624274522918912",1,"","","Nach Bürgergespräch bin nun noch im Ratshof zur Ausstellungseröffnung - Wanderausstellung zum Bundestag."
"530357749188923392",2,"","","Streiks müssen Auswirkungen haben - und die #bahn verletzt täglich Verbraucherinteressen: URL #gdlstreik #gdl #db "
"465846218858708992",2,"","","RT @bioland_de: Wieso sollen Biobauern dafür bestraft werden, dass sie KEINE Pestizide einsetzen? Genau das hat die EU vor: URL "
"543111899794407426",2,"","","RT @DanielLuecking: #NSAUA @Peter_Schaar Verhältnismäßigkeit muss hinterfragt werden - Grundrechtsverletzungen durch Überwachung gehören au… "
1 532463690013233152 1 RT @cordhos: ! “@cducsubt: Paul Breitner vom @FCBayern - #Bundestag jetzt mit eigenem Fanclub @hahnflo @DoroBaer @dieAlbsteigerin http://t.…
2 516584367448403968 1 Debate und critics in the parlamentarian assembly of the European Council about the elections in #Turkey @PACE_News @GeziParkii
3 516624274522918912 1 Nach Bürgergespräch bin nun noch im Ratshof zur Ausstellungseröffnung - Wanderausstellung zum Bundestag.
4 530357749188923392 2 Streiks müssen Auswirkungen haben - und die #bahn verletzt täglich Verbraucherinteressen: URL #gdlstreik #gdl #db
5 465846218858708992 2 RT @bioland_de: Wieso sollen Biobauern dafür bestraft werden, dass sie KEINE Pestizide einsetzen? Genau das hat die EU vor: URL
6 543111899794407426 2 RT @DanielLuecking: #NSAUA @Peter_Schaar Verhältnismäßigkeit muss hinterfragt werden - Grundrechtsverletzungen durch Überwachung gehören au…
issuecomp-codingsample-error2.csv
+1
View File
@@ -0,0 +1 @@
"530357749188923392","","labor.504","","Streiks müssen Auswirkungen haben - und die #bahn verletzt täglich Verbraucherinteressen: URL #gdlstreik #gdl #db "
1 530357749188923392 labor.504 Streiks müssen Auswirkungen haben - und die #bahn verletzt täglich Verbraucherinteressen: URL #gdlstreik #gdl #db
issuecomp-functions.R
+11 -7
View File
@@ -27,16 +27,20 @@ convertLogical0 <- function(var) {
}
smartPatternMatch <- function(string, pattern, chars, acronym) {
pattern <- str_c("\\b", pattern, "\\b")
patternrex <- str_c("\\b", pattern, "\\b")
if(chars <= 4) {
found <- agrep(pattern, string, max.distance = list(all = 0), ignore.case = !acronym, fixed = FALSE)
if(chars <= 4) { # 4 or less
found <- agrep(patternrex, string, max.distance = list(all = 0), ignore.case = !acronym, fixed = FALSE)
}
else if(chars >= 8) {
found <- agrep(pattern, string, max.distance = list(all = 2), ignore.case = !acronym, fixed = FALSE)
else if(chars >= 8) { # 8 or more
found <- agrep(patternrex, string, max.distance = list(all = 3), ignore.case = !acronym, fixed = FALSE)
# Give longer words a chance by ignoring word boundaries \\b
if(convertLogical0(found) == 0) {
found <- grep(pattern, string, ignore.case = !acronym, fixed = FALSE)
}
}
else {
found <- agrep(pattern, string, max.distance = list(all = 1), ignore.case = !acronym, fixed = FALSE)
else { # 5,6,7
found <- agrep(patternrex, string, max.distance = list(all = 2), ignore.case = !acronym, fixed = FALSE)
}
found <- convertLogical0(found)
return(found)
issues.xml
+1 -1
View File
@@ -1,4 +1,5 @@
<issuelist>
# Makroökonomie
<macro.100>
<tag>Wirtschaft</tag>
<tag>Wirtschaftswachstum</tag>
@@ -68,7 +69,6 @@ KFZ-Steuer
<tag>Rassismus</tag>
<tag>rassistisch</tag>
<tag>Rechtsextremismus</tag>
<tag>Nazi</tag>
<tag>Nazis</tag>
</civil.201>
<civil.206>