Uses the twitteR and SentimentAnalysis package to grab tweets over the last 7 days mentioning 'stock market' and extract sentiment

Stock_Tweets.R

library(twitteR)
library(tm)
library(SentimentAnalysis)


setup_twitter_oauth(consumer_key = ,
                    consumer_secret =,
                    access_token = ,
                    access_secret = )

days <- seq.Date(from=as.Date("2018-01-31"), to= as.Date("2018-02-07"), by="day")



sent <- matrix(NA, nrow=(length(days)-1), ncol=4)
se <- matrix(NA, nrow=(length(days)-1), ncol=4)

tweet.store <- list()

for(ii in 2:length(days)){
  tweets <- searchTwitter("stock market", n =500, lang="en", resultType = "mixed", 
                          since=as.character(days)[ii-1], 
                          until=as.character(days)[ii])
  tweet.store[[ii-1]] <- tweets
  fn <- unlist(lapply(tweets, function(x) x$text))
  
  fn <- gsub('http.*\\s*', '', fn)
  fn <- gsub('@\\S+\\s*', '', fn)
  fn <- gsub('#', '', fn)
  fn <- iconv(fn, "latin1", "ASCII", sub="")
  
  
  
  vs <- VectorSource(fn)
  corp <- Corpus(vs)
  dtm <- toDocumentTermMatrix(corp)
  
  out <- analyzeSentiment(corp)
  
  sent[ii-1,1] <- mean(out$SentimentGI, na.rm=T)
  se[ii-1, 1] <- sd(out$SentimentGI, na.rm=T)
  
  sent[ii-1,2] <- mean(out$SentimentHE, na.rm=T)
  se[ii-1, 2] <- sd(out$SentimentHE, na.rm=T)
  
  sent[ii-1,3] <- mean(out$SentimentLM, na.rm=T)
  se[ii-1, 3] <- sd(out$SentimentLM, na.rm=T)
  
  sent[ii-1,4] <- mean(out$SentimentQDAP, na.rm=T)
  se[ii-1, 4] <- sd(out$SentimentQDAP, na.rm=T)
  
  
}


#png("twitter_stock.png", height=6, width=6, 
#    res=400, units='in')
plot.new()
plot.window(ylim=c(-.10, 0.10), xlim=c(1, length(days)-1))


rect(xleft=2.5, xright=3.5, ybottom = -1, ytop=1,
     col=ggplot2::alpha("red", .25), border=NA)

for(ii in 1:(length(days)-1)){
  points(y=sent[ii, 1], x=ii, lwd=2)
  lines(y=sent[ii, 1] + c(se[ii, 1], -se[ii,1])/sqrt(500), x=c(ii,ii), lwd=2)
}
axis(2)

box()
axis(1, at=1:7, labels=format(days[-7], "%b %d"))

abline(h=0, lty=2)
title(main="Sentiment of Tweets mentioning 'stock market'", 
      xlab="Day", ylab="Sentiment")
#dev.off()