62 lines
1.9 KiB
R
62 lines
1.9 KiB
R
require(lubridate)
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# Create date range
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date_start <- as.Date("2014-01-01")
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date_end <- as.Date("2014-12-01")
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drange <- as.integer(date_end - date_start)
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drange <- date_start + days(0:d)
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issues <- data.frame(date = drange)
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issuelist <- xmlToList("issues.xml")
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issueheads <- names(issuelist)
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issues[issueheads] <- 0
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for(d in 1:nrow(issues)) {
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curdate <- issues$date[d]
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cat(as.character(curdate),"\n")
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# Put all tweets from specific day in a temporary DF
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tweets_curday <- tweets[tweets[, "created_at"] == curdate, ]
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for(t in 1:nrow(tweets_curday)){
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# Select tweet's text, make it lowercase and remove hashtag indicators (#)
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curtext <- tolower(as.character(tweets_curday$text[t]))
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curtext <- str_replace_all(curtext, "#", "")
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for(i in 1:length(issuelist)) {
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curtags <- as.character(issuelist[[i]])
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curissue <- names(issuelist)[i]
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curtags <- str_c("\\W", curtags, "\\W")
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tags_found <- str_detect(curtext, sprintf("%s", curtags))
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tags_found <- any(tags_found)
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if(tags_found) {
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#cat("Positive in", curissue,"from",as.character(drange[d]),"\n")
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issues[d,curissue] <- issues[d,curissue] + 1
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}
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else {
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#cat("Nothing found\n")
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}
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} # /for issuelist
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} # /for tweets_curday
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} # /for drange
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# VISUALS -----------------------------------------------------------------
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library(ggplot2)
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library(reshape2)
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df <- melt(issues,id="date")
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ggplot(df,aes(x=date,y=value,colour=variable,group=variable)) + geom_line()
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ggplot(df,aes(x=date,y=value,colour=variable,group=variable)) + geom_smooth(size=0.5,method="loess",formula = y ~ x, se=FALSE)
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# POSSIBLY USEFUL CODE ----------------------------------------------------
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# Limits of list
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length(issuelist)
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length(issuelist[[2]])
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# Select all tweets from current day in drange
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tweets_curday <- tweets[tweets[, "created_at"] == drange[5], ]
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# Is column a issue counting column?
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str_detect(names(issues[2]), "^issue") |