Inside the Underground Market for Fake Amazon Reviews

Another recommended tactic is to leave negative reviews on other products to give a more genuine appearance to a reviewer’s profile. Many of these reviewers are folks that already shop on Amazon, including Prime members, who are tempted by the promise of a freebie.

Gaming the System

Precisely how Amazon’s star ratings are calculated is a secret. The company uses a proprietary machine-learning model that includes multiple factors, including the reviewer’s past behavior, whether purchases are verified, and how recent a review is. Its detection model for fake reviews has undoubtedly improved over the years, but so have the scammer’s techniques.

Review farms used to use Markov chain generators—an algorithm that can create rudimentary sentences by using common phrases and probability to predict sentence structures. That’s according to Saoud Khalifah, the founder of Fakespot, a company that detects fake reviews and scams. “Today, they’re using machine-learning models working from scraped data to scan old reviews and respin the words.”

Courtesy of Rajvardhan Oak

Khalifah started Fakespot from his bedroom after buying a five-star-rated supplement and receiving a product that “looked like someone made it in a garage as a side project.” He began by creating a program that could detect text generators but later began to stir in other attributes found in fake reviews. He set up a website, passed it around to friends and family, and before long he quit his software engineer job at Goldman Sachs to go full time into Fakespot.

You can download the Fakespot app for Android and iOS, or add it to your browser, and use it to analyze reviews across a variety of retailers, including Amazon, Best Buy, eBay, and Walmart. Khalifah says Fakespot employs 20 to 30 machine-learning models when it analyzes a listing and has more than 12 billion reviews in its database. Each model focus on a particular attribute: One assesses how people write, another identifies links to promotional groups, and yet another dives deep into the reviewer’s profile. The secret sauce is that Fakespot can track reviewers across platforms.

Some fraudsters are using these automated systems, but Khalifah acknowledges there’s not much Fakespot can do with fake review recruitment across social media, whether you’re on Facebook, Twitter, or Telegram. It’s a problem Amazon has been fighting for years.

“We have teams dedicated to uncovering and investigating fake reviews brokers,” an Amazon spokesperson tells WIRED. “Our expert investigators, lawyers, analysts, and other specialists track down brokers, piece together evidence about how they operate, and then we take legal actions against them. We are committed to keeping reviews trustworthy in our stores, and this strategy of shutting down fraudsters is working.”

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