Rajesh Peruri analyzed a dataset containing client feedback comments and recommended scores (RECOM) to predict RECOM using sentiment analysis of the comments. The analysis included: determining sentiment scores of comments using association matrices and clustering; and building a linear regression model relating RECOM to other variables and sentiment. Rajanikar performed sentiment analysis of comments by assigning sentiment scores to words based on a dictionary and identifying sentiment polarity. Priyadarshini used a sentiment algorithm to assign integer sentiment scores to comments and analyzed the distribution and relationship of sentiment scores and average ratings scores.