Dictionary based scoring

As described in the steps we outlined for our approach, let us use a sentiment dictionary to score our initially extracted tweets. We are going to leverage the sentimentr R package to learn the sentiments of the tweets we have collected.

Let us see how to score using the sentiment function from the sentimentr package: 

> library(sentimentr, quietly = TRUE)
> sentiment.score <- sentiment(tweet.df$text)
> head(sentiment.score)
   element_id sentence_id word_count  sentiment
1:          1           1          8  0.0000000
2:          2           1          8  0.3535534
3:          3           1          3  0.0000000
4:          3           2          4  0.0000000
5:          3           3          7  0.0000000
6:          4           1         14 -0.8418729

The sentiment function in sentimentr calculates a score between -1 and 1 for each of the tweets. In fact, if a tweet has multiple sentences, it will calculate the score for each sentence. A score of -1 indicates...