Michael Luca

Georgios Zervas

Consumer reviews are now a part of everyday decision-making. Yet, the credibility of reviews is fundamentally undermined when business-owners commit review fraud, either by leaving positive reviews for themselves or negative reviews for their competitors. In this paper, we investigate the extent and patterns of review fraud on Yelp, a popular consumer review platform. Because one cannot directly observe which reviews are fake, we focus on reviews that Yelp's algorithmic indicator has identified as fraudulent. Using this proxy, we present four main findings. First, roughly 16% of restaurant reviews on Yelp are identified as fraudulent, and tend to be more extreme (favorable or unfavorable) than other reviews. Second, a restaurant is more likely to commit review fraud when its reputation is weak, i.e., when it has few reviews, or it has recently received bad reviews. Third, chain restaurants - which benefit less from Yelp - are also less likely to commit review fraud. Fourth, when restaurants face increased competition, they become more likely to receive unfavorable fake reviews. To reinforce our interpretation that fake reviews are driven by economic incentives, we then collect a second data set of businesses that were caught soliciting fake reviews through a sting conducted by Yelp. Results from these data are consistent with our main results, further identifying economic incentives behind a business's decision to leave fake reviews. Taken in aggregate, these findings highlight the extent of review fraud and suggest that a business's decision to commit review fraud responds to competition and reputation incentives.

Georgios Zervas

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