Dai, Weijia. <br/><br/>
Aggregation of Consumer Ratings:  An Application to Yelp.com / 
Weijia Dai, Ginger Z. Jin, Jungmin Lee, Michael Luca. 
 - Cambridge, Mass.  National Bureau of Economic Research  2012. 
 - 1 online resource:  illustrations (black and white); 
 - NBER working paper series  no. w18567 .
 - Working Paper Series (National Bureau of Economic Research)  no. w18567. .
<br/><br/> November 2012. 
<br/><br/> 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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