Understanding rating behavior based on moral foundations: The case of Yelp reviews
Pegah Nokhiz, Fengjun Li · 2017
Moral inclinations expressed in user-generated content such as online reviews can provide useful insight to understand and predict people's rating behavior. In this work, we extracted a corpus of over 7,000 online reviews on Yelp that express moral concerns, and associated them to five moral factors defined in Moral Foundations Theory using the Doc2Vec natural language processing technique. We compared the rating distributions between the regular reviewers and the moral-concerned reviewers, and found that their rating patterns significantly differ from each other. Our findings also indicate that people with moral concerns tend to rate lower if a moral foundation is violated. Moreover, among the five moral factors, purity is the most distinctive moral foundation.