When it comes to scouting out a new bakery, pizzeria or noodle shop, there are few review sites that compare to Yelp. In turn, the reviews left on sites like Yelp can have a big effect on many restaurants’ bottom lines.
That’s created a huge incentive for businesses to write fake positive reviews about themselves, called “astroturfing.” Some fake reviews are written by the businesses, while others are produced in bulk by reputation management companies. Michael Luca of the Harvard Business School and Georgios Zervas of Boston University wanted to figure out the exact conditions under which companies have strongest incentive to leave a fake review.
Luca and Zervas analyzed 316,415 reviews for 3,625 Boston-area restaurants written between 2004 through 2012, all of which Yelp had already flagged as potentially fraudulent. These “filtered” reviews make up about 25 percent of the 42 million total reviews submitted for all businesses. Luca and Zervas found 16 percent of reviews for Boston restaurants weren’t legitimate.
But defining fraudulence is tricky, especially since Luca and Zervas don’t know exactly what makes Yelp’s private algorithm tick. According to guidelines from the Federal Trade Commission, a review written by the business owner, family members, competitors or a compensated reviewer would be considered false advertising. But an owner who encourages users to review his restaurant (and provides instructions) falls into a grey area.
Luca and Zervas’ study, which is currently being reviewed by a journal for publication, draws a few large conclusions about who cheats and why. They found that restaurants that have a “weak” reputation (few and/or poor reviews) are more likely to boost their presence with fake positive reviews. Those that faced more regional competition might write positive reviews for themselves and leave negative reviews for competitors. Luca and Zervas also found that chain restaurants, which do not benefit greatly from Yelp, are less likely to commit review fraud.
Luca says he was surprised to find that ethics had nothing to do with it.
“This type of decision was influenced by the amount of competition and incentives,” he says. “This wasn’t just a story of a few rotten apples that were going to leave a bad review no matter what.”
The number of posts Yelp has to filter has increased dramatically in its nine-year existence. Luca says its part of an “arms race” between the review sites and scammers.
“People are finding increasing sophisticated ways to get around the algorithms,” he says. And, as Zervas told Boston University, as more consumers make decisions with on crowd-sourced reviews, businesses have a higher incentive to cheat.
But those developing the algorithms are also creating new tools that might make fake reviews less relevant in the first place. Luca’s next project is working with health inspectors to tap into a restaurant’s reviews and predict which ones might have hygiene violations.
If a restaurant’s Yelp page is branded with a “pest infestation” alert, it might be hard to distract with the fake review: “Great nachos, fast service.”
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