What factors affect consumers' dining sentiments and their ratings: Evidence from restaurant online review data

摘要

Online review data refers to customer opinions (e.g., text reviews, numerical ratings, and personal information) left on online retailing and review platforms. Here, we provide insight for food-related consumer sentiment study by using online review data. We present a case study using Yelp restaurant review data on what affects restaurant customers' sentiment responses to dining out. In our case study, a sentiment-analysis method was used to extract and generate sentiment indices from 175,879 text-based Yelp restaurant reviews. We examined the relationships between our sentiment indices and ratings and showed that online review data can provide information about consumer dining sentiments. By using semi-automatic content analysis method, we first counted the most frequent 300 words in all text reviews and manually categorized those most frequent words into five topics: "food," "service," "expenditure," "social," and "miscellany". We then computed the fraction of topic words in each category over the total topic words for each review. We found that (1) consumers used more positive sentiment words than negative sentiment words in their Yelp restaurant text reviews. (2) The proportion of positive sentiment words in reviews was positively related to ratings; the proportion of negative sentiment words in reviews was negatively related to ratings. (3) Relative to food, consumers used more sentiment words (both positive and negative) when they were discussing restaurant service. (4) Consumers used the least sentiment words when they were discussing social-related topics compared with the other topics (food, service and expenditure). (5) Consumers rated restaurant service higher than they rated food.