Restaurant Rating: Industrial Standard and Word-of-Mouth -- A Text Mining and Multi-dimensional Sentiment Analysis

摘要

AAA Restaurant Diamond Rating Guidelines (which is regarded as industry standards) rate a restaurant in three aspects: food, service, and décor/ambience. Drawing upon extant literature, we argue that special contexts and pricing are two other major aspects in restaurant rating in addition to aforementioned three aspects. We tested our hypotheses based on our text mining and sentiment analysis of 268, 442 customer reviews of 7, 508 restaurants on Yelp.com, A form of digital word-of-mouth. Results from fitting a multilevel model showed that the sentiments about each of these five aspects alone explained about 28% of the explainable between-restaurant variances, and 12% of the explainable within-restaurant variances of the restaurants' star ratings. With other level and control variables, the multilevel model can explain more than 53% between-restaurant variances and 28% within-restaurant variances.