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来源类型Working Paper
规范类型报告
DOI10.3386/w18567
来源IDWorking Paper 18567
Aggregation of Consumer Ratings: An Application to Yelp.com
Weijia Dai; Ginger Z. Jin; Jungmin Lee; Michael Luca
发表日期2012-11-29
出版年2012
语种英语
摘要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.
主题Microeconomics ; Economics of Information ; Industrial Organization ; Market Structure and Firm Performance ; Industry Studies
URLhttps://www.nber.org/papers/w18567
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/576242
推荐引用方式
GB/T 7714
Weijia Dai,Ginger Z. Jin,Jungmin Lee,et al. Aggregation of Consumer Ratings: An Application to Yelp.com. 2012.
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