Optimal Aggregation of Consumer Ratings: An Application to Yelp.com

Consumer review websites leverage the wisdom of the crowd, with each product being reviewed many times (some with more than 1,000 reviews). Because of this, the way in which information is aggregated is a central decision faced by consumer review websites. Given a set of reviews, what is the optimal...

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Bibliographic Details
Published in:NBER Working Paper Series 2012-11, p.18567
Main Authors: Dai, Weijia, Jin, Ginger Z, Lee, Jungmin, Luca, Michael
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Consumers
Economic models
Economic statistics
Economic theory
Economics
Product quality
Product reviews
Ratings & rankings
Restaurants
Studies
Websites
Online Access:Get full text
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Summary:Consumer review websites leverage the wisdom of the crowd, with each product being reviewed many times (some with more than 1,000 reviews). Because of this, the way in which information is aggregated is a central decision faced by consumer review websites. Given a set of reviews, what is the optimal way to construct an average rating? We offer a structural approach to answering this question, allowing for (1) reviewers to vary in stringency and accuracy, (2) reviewers to be influenced by existing reviews, and (3) product quality to change over time.
ISSN:0898-2937
DOI:10.3386/w18567