Controlling Fake Reviews

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See all articles by Yuta Yasui

Yuta Yasui

University of California, Los Angeles (UCLA)

Date Written: September 21, 2020


In this study, I theoretically analyze fake reviews on a platform market using models where a seller creates fake reviews through incentivized transactions, and its sales depend on its rating based on a review history. The platform can control the incentive for fake reviews by changing the parameters of the rating system, such as its filtering policy and weights, for past reviews. At equilibrium, the number of fake reviews increases as quality increases but decreases as reputation improves. Since fake reviews have a positive relationship with a product’s underlying quality, under some parameters, rational consumers find a rating more informative when fake reviews exist, while credulous consumers suffer from a bias caused by boosted reputation. A stringent filtering policy can decrease the expected amount of fake reviews and the bias of credulous consumers, but at the same time, it can decrease the informativeness of a rating system for rational consumers. In terms of the weight placed on the review history, rational consumers benefit from higher weights on past reviews than from optimal weights without fake reviews.

Keywords: fake review, reputation, rating design

JEL Classification: D49, L51, M37

Suggested Citation

Yasui, Yuta, Controlling Fake Reviews (September 21, 2020). Available at SSRN:

Yuta Yasui (Contact Author)

University of California, Los Angeles (UCLA) ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095
United States

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