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# Sentiment analysis
tknDct <- tokens_lookup(tkn, dictionary = data_dictionary_LSD2015)
saDfm <- dfm(tknDct,
remove = stopwords("en"),
stem = T)
summ <- do.call("rbind", by(convert(saDfm, to="data.frame")[,-1],
INDICES = date(tweetReduced$created_at),
FUN = colSums))
dev.off() # reset past graphical pars
plot(date(rownames(summ)),
(summ[,2] - summ[,1]) / rowSums(summ[,1:2]),
type = "l", xlab = "Date", ylab = "Sentiment score")
abline(h = 0)
abline(v = date(epAirTime), lty = 2, col = rgb(1,0,0,.5))
text(date(epAirTime) - 3, .095, labels = paste0("Ep.", c(1:6)))
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