NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Aggregation of Consumer Ratings: An Application to Yelp.com

Weijia Dai, Ginger Z. Jin, Jungmin Lee, Michael Luca

NBER Working Paper No. 18567
Issued in November 2012, Revised in February 2018
NBER Program(s):Industrial Organization

Because consumer reviews leverage the wisdom of the crowd, the way in which they are aggregated is a central decision faced by platforms. We explore this "rating aggregation problem" and offer a structural approach to solving it, 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. Applying this to restaurant reviews from Yelp.com, we construct an adjusted average rating and show that even a simple algorithm can lead to large information efficiency gains relative to the arithmetic average.

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Document Object Identifier (DOI): 10.3386/w18567

forthcoming in Quantitative Marketing and Economics.

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