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A Text Mining and Multidimensional Sentiment Analysis of Online Restaurant Reviews

Journal of Quality Assurance in Hospitality & TourismPublished 14 December 2016
Qiwei Gan, Bo H. Ferns, Yang Yu, Lei Jin
Citations142
SJR quartileQ2
SJR score0.65
SNIP1.09

TL;DR

Results showed that consumers’ sentiments in these five attributes significantly explained the differences in star ratings.

Abstract

This study aims to identify the structure of online restaurant reviews and examine the influence of review attributes and sentiments on restaurant star ratings. While past research indicated four attributes specific to restaurant reviews—food, service, ambience, and price—this study proposes context as the fifth attribute unique to online reviews. Sentiment analysis of online restaurant reviews has confirmed the proposed underlying structure of online restaurant reviews. Results showed that consumers' sentiments in these five attributes significantly explained the differences in star ratings. Food, service, and context are the top three attributes affecting star ratings, followed by price and ambiance.

Keywords

Social SciencesBusiness, Management and Accounting