Exploring the Correlation Between Ratings, Adjectives and Sentiment on Customer Reviews

Abstract: Customer reviews are important for both customers and companies. Customers want to find out if the product or service is what they need while companies want to figure out if their product is good enough for their customers. There is, however, an issue where customers very rarely write a product review. An example of a solution for this could be to let the customer choose between adjectives rather than write the entire review. To help future researchers find out if this could make customers more prone to write reviews, this study looks at the correlation between the sentiment and the rating, as well as the adjectives used when a rating and sentiment correlate. Other studies look at the correlation, or the precision of the tool used for sentiment analysis but do not go in-depth on what makes a review correlate with its rating. To study this, four datasets of reviews were used with a total of 105234 reviews. Then, using Stanford CoreNLP each review text got a predicted sentiment score. The Pearson coefficient was then used to find the correlation coefficient between ratings and sentiments. The conclusion is that there is a weak-moderate correlation between ratings and sentiment. Adjectives with a positive sentiment had a higher correlation than negative adjectives, however, most of them still had a low correlation. The sentiment correlates better when the reviews with only one sentence are omitted from the result.