Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud
Consumer reviews are now part of everyday decision-making. Yet, the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves or their competitors. We investigate the economic incentives to commit review fraud on the popular review platform Yelp, using two complementary approaches and datasets. We begin by analyzing restaurant reviews that are identified by Yelp's filtering algorithm as suspicious, or fake ? and treat these as a proxy for review fraud (an assumption we provide evidence for). We present four main findings. First, roughly 16% of restaurant reviews on Yelp are filtered. These reviews tend to be more extreme (favorable or unfavorable) than other reviews, and the prevalence of suspicious reviews has grown significantly over time. 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. Using a separate dataset, we analyze businesses that were caught soliciting fake reviews through a sting conducted by Yelp. These data support our main results, and shed further light on the economic incentives behind a business's decision to leave fake reviews.
|Date of creation:||Jul 2013|
|Date of revision:||May 2015|
|Contact details of provider:|| Postal: Soldiers Field, Boston, Massachusetts 02163|
Web page: http://www.hbs.edu/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Dina Mayzlin & Yaniv Dover & Judith A. Chevalier, 2012. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," NBER Working Papers 18340, National Bureau of Economic Research, Inc.
- Weijia Dai & Ginger Z. Jin & Jungmin Lee & Michael Luca, 2012.
"Optimal Aggregation of Consumer Ratings: An Application to Yelp.com,"
NBER Working Papers
18567, National Bureau of Economic Research, Inc.
- Weijia Dai & Ginger Jin & Jungmin Lee & Michael Luca, 2012. "Optimal Aggregation of Consumer Ratings: An Application to Yelp.com," Harvard Business School Working Papers 13-042, Harvard Business School, revised Oct 2014.
- Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
- Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
- Bryan Bollinger & Phillip Leslie & Alan Sorensen, 2011. "Calorie Posting in Chain Restaurants," American Economic Journal: Economic Policy, American Economic Association, vol. 3(1), pages 91-128, February.
- Bollinger, Bryan & Leslie, Phillip & Sorensen, Alan, 2010. "Calorie Posting in Chain Restaurants," Working Papers 56693, American Association of Wine Economists.
- Bryan Bollinger & Phillip Leslie & Alan Sorensen, 2010. "Calorie Posting in Chain Restaurants," NBER Working Papers 15648, National Bureau of Economic Research, Inc.
- Mark Duggan & Steven D. Levitt, 2002. "Winning Isn't Everything: Corruption in Sumo Wrestling," American Economic Review, American Economic Association, vol. 92(5), pages 1594-1605, December.
- Mark Duggan & Steven D. Levitt, 2000. "Winning Isn't Everything: Corruption in Sumo Wrestling," NBER Working Papers 7798, National Bureau of Economic Research, Inc.
- Xinxin Li & Lorin M. Hitt, 2008. "Self-Selection and Information Role of Online Product Reviews," Information Systems Research, INFORMS, vol. 19(4), pages 456-474, December.
- Hausman, J. A. & Abrevaya, Jason & Scott-Morton, F. M., 1998. "Misclassification of the dependent variable in a discrete-response setting," Journal of Econometrics, Elsevier, vol. 87(2), pages 239-269, September.
- Michael Anderson & Jeremy Magruder, 2012. "Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database," Economic Journal, Royal Economic Society, vol. 122(563), pages 957-989, 09.
- Ginger Zhe Jin & Phillip Leslie, 2009. "Reputational Incentives for Restaurant Hygiene," American Economic Journal: Microeconomics, American Economic Association, vol. 1(1), pages 237-267, February.
- Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
- David Godes & José C. Silva, 2012. "Sequential and Temporal Dynamics of Online Opinion," Marketing Science, INFORMS, vol. 31(3), pages 448-473, May. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:hbs:wpaper:14-006. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Soebagio Notosoehardjo)
If references are entirely missing, you can add them using this form.