Aggregation of Consumer Ratings: An Application to Yelp.Com

59 Pages Posted: 30 Nov 2012

See all articles by Daisy Dai

Daisy Dai

Lehigh University

Ginger Zhe Jin

University of Maryland - Department of Economics; National Bureau of Economic Research (NBER)

Jungmin Lee

Seoul National University

Michael Luca

Harvard Business School

Multiple version iconThere are 2 versions of this paper

Date Written: November 2012

Abstract

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.

Suggested Citation

Dai, Daisy and Jin, Ginger Zhe and Lee, Jungmin and Luca, Michael, Aggregation of Consumer Ratings: An Application to Yelp.Com (November 2012). NBER Working Paper No. w18567. Available at SSRN: https://ssrn.com/abstract=2183028

Daisy Dai (Contact Author)

Lehigh University ( email )

621 Taylor Street
Bethlehem, PA 18015
United States

Ginger Zhe Jin

University of Maryland - Department of Economics ( email )

College Park, MD 20742
United States
301-405-3484 (Phone)
301-405-3542 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Jungmin Lee

Seoul National University ( email )

Kwanak-gu
Seoul, 151-742
Korea, Republic of (South Korea)

Michael Luca

Harvard Business School ( email )

Soldiers Field Road
Boston, MA 02163
United States

HOME PAGE: http://drfd.hbs.edu/fit/public/facultyInfo.do?facInfo=ovr&facId=602417

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