Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud

References

• Akoglu L, Chandy R, Faloutsos C (2013) Opinion fraud detection in online reviews by network effects. Proc. 7th Internat. AAAI Conf. Weblogs and Soc. Media (Association for the Advancement of Artificial Intelligence, Palo Alto, CA), 2–11.Google Scholar
• Anderson ET, Simester DI (2014) Reviews without a purchase: Low ratings, loyal customers, and deception. J. Marketing Res. 51(3):249–269.Crossref, Google Scholar
• Auty S (1992) Consumer choice and segmentation in the restaurant industry. Service Industries J. 12(3):324–339.Crossref, Google Scholar
• Bollinger B, Leslie P, Sorensen A (2010) Calorie posting in chain restaurants. Technical report (National Bureau of Economic Research, Cambridge, MA).Google Scholar
• Branco F, Villas-Boas JM (2015) Competitive vices. J. Marketing Res. 52(6):801–816.Crossref, Google Scholar
• Chevalier Ja, Mayzlin D (2006) The effect of word of mouth on sales: Online book reviews. J. Marketing Res. 43(3):345–354.Crossref, Google Scholar
• Duggan M, Levitt SD (2002) Winning isn’t everything: Corruption in sumo wrestling. Amer. Econom. Rev. 92(5):1594–1605.Crossref, Google Scholar
• Federal Trade Commission (2009) Guides concerning the use of endorsements and testimonials in advertising, 16 CFR Part 255; http://ftc.gov/os/2009/10/091005revisedendorsementguides.pdf.Google Scholar
• Feng S, Banerjee R, Choi Y (2012) Syntactic stylometry for deception detection. Proc. 50th Annual Meeting Assoc. Computational Linguistics (Association for Computational Linguistics, Stroudsburg, PA), 171–175.Google Scholar
• Gao GG, Greenwood BN, Agarwal R, McCullough J (2015) Vocal minority and silent majority: How do online ratings reflect population perceptions of quality? MIS Quart. 39(3):565–589.Crossref, Google Scholar
• Hu N, Pavlou PA, Zhang J (2006) Can online reviews reveal a product’s true quality? Empirical findings and analytical modeling of online word-of-mouth communication. Proc. 7th ACM Conf. Electronic Commerce (Association for Computing Machinery, New York), 324–330.Crossref, Google Scholar
• Jin G, Leslie P (2009) Reputational incentives for restaurant hygiene. Amer. Econom. J. Microeconomics 1(1):237–267.Crossref, Google Scholar
• Jindal N, Liu B, Lim EP (2010) Finding unusual review patterns using unexpected rules. Proc. 19th ACM Internat. Conf. Inform. Knowledge Management (Association for Computing Machinery, New York), 1549–1552.Crossref, Google Scholar
• Li X, Hitt LM (2008) Self-selection and information role of online product reviews. Inform. Systems Res. 19(4):456–474.Link, Google Scholar
• Luca M (2011) Reviews, reputation, and revenue: The case of Yelp.com. HBS Working Paper 12-016, Harvard Business School, Cambridge, MA.Google Scholar
• Luca M (2015) User-generated content and social media. Anderson SP, Stromberg D, Waldfogel J, eds. Handbook of Media Economics, Vol. 1A, Chap. 12 (Elsevier, Amsterdam).Crossref, Google Scholar
• Mayzlin D, Dover Y, Chevalier J (2014) Promotional reviews: An empirical investigation of online review manipulation. Amer. Econom. Rev. 104(8):2421–55.Crossref, Google Scholar
• Mukherjee A, Liu B, Glance N (2012) Spotting fake reviewer groups in consumer reviews. Proc. 21st Internat. Conf. World Wide Web (Association for Computing Machinery, New York), 191–200.Crossref, Google Scholar
• Mukherjee A, Liu B, Wang J, Glance N, Jindal N (2011) Detecting group review spam. Proc. 20th Internat. Conf. Companion on World Wide Web (Association for Computing Machinery, New York), 93–94.Crossref, Google Scholar
• Mundlak Y (1978) On the pooling of time series and cross section data. Econometrica: J. Econometric Soc. 46(1):69–85.Crossref, Google Scholar
• Ott M, Cardie C, Hancock J (2012) Estimating the prevalence of deception in online review communities. Proc. 21st Internat. Conf. World Wide Web (Association for Computing Machinery, New York), 201–210.Crossref, Google Scholar
• Parsa H, Self JT, Njite D, King T (2005) Why restaurants fail. Cornell Hotel Restaurant Admin. Quart. 46(3):304–322.Crossref, Google Scholar
• Segal D (2011) A rave, a pan, or just a fake? New York Times (May 21), http://www.nytimes.com/2011/05/22/your-money/22haggler.html.Google Scholar
• Singley E (2012) Consumer alerts: Because you might like to know. Yelp (blog) (October 18), http://officialblog.yelp.com/2012/10/consumer-alerts-because-you-might-like-to-know.html.Google Scholar
• Smith D (2004) Amazon reviewers brought to book. The Guardian (February 14), http://www.guardian.co.uk/technology/2004/feb/15/books.booksnews.Google Scholar
• Von Ahn L, Blum M, Hopper NJ, Langford J (2003) CAPTCHA: Using hard AI problems for security. Biham E, ed. Advances in Cryptology-EUROCRYPT 2003 (Springer, Berlin), 294–311.Crossref, Google Scholar
• Wand MP, Jones MC (1995) Kernel Smoothing, Vol. 60 (Chapman & Hall/CRC, Boca Raton, FL).Crossref, Google Scholar