Use python programming language to write a program that computes the sentiments of each of the 100 reviews. You will find a zipped file containing 100 reviews from Yelp.
There are several ways to do this:
1. Use the AFFIN-111.txt file on Blackboard to get words and their associated sentiment. For each Yelp review, iterate through the words and get the cumulative sentiment score.
2. You may use Textblob to compute the sentiment score for each Yelp review.
3. NLTK has something called SentimentIntensityAnalyzer (see my slides for an example) to compute sentiments.
Use any two of the approaches shown above to compute the sentiments of each of the 100 Yelp reviews. A sample output using AFFIN-111.txt and Textblob will be as follows:
Review AFFIN-Sentiment Textblob-Sentiment
1 8 0.7
2 -3 -0.16
Link to the 100 yelp reviews : https://elearn.uta.edu/bbcswebdav/pid-7188776-dt-content-rid-131820819_2/xid-131820819_2
Link to the AFFIN-111.txt file: https://drive.google.com/open?id=18RW1L_Tm6fHGlMFK4KlEVWoKdC7AhH2d