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Inside the Underground Market for Fake Amazon Reviews

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Another recommended practice is to leave negative reviews on other products to make your reviewer profile look more authentic. Many of these reviewers are people who have already shopped on Amazon, including Prime members lured by the promise of freebies.

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exactly how Amazon star rating It is a secret that is calculated. The company uses a proprietary machine learning model that includes multiple factors such as the reviewer’s past behavior, whether the purchase is confirmed and how recent the review is. Fake review detection models have definitely improved over the years, but scammer techniques have improved as well.

Check the farm used to use the Markov chain generator. create a rudimentary sentence using common phrases and probabilities predict sentence structureAccording to founder Saud Khalifa, fake spot, a company that detects fake reviews and fraud. “Today, they are using machine learning models from scraped data to scan old reviews and re-spun words.”

Courtesy of Rajvardhan Oak

Khalifah started Fakespot from his bedroom after purchasing a five-star rated supplement and receiving a product that “looks like someone made it in a garage as a side project.” He started by writing a program that could detect the text his generator, but later began churning out other attributes found in fake reviews. He launched the website, told it to his friends and family, and eventually quit his software engineer job at Goldman Sachs to join Fakespot full-time.

You can download the Fakespot app for Android and iOS or add it to your browser and use it to analyze reviews from various retailers like Amazon, Best Buy, eBay, Walmart and more. Khalifah said Fakespot uses 20-30 machine learning models when analyzing listings and has over 12 billion reviews in his database. Each model focuses on specific attributes. One evaluates how people write, another identifies links to promotional groups, and another digs deep into reviewer profiles. The secret sauce is that Fakespot can track reviewers across multiple platforms.

While some scammers use these automated systems, Khalifah is against soliciting fake reviews across social media, whether they use Facebook, Twitter, or Telegram. This is a problem Amazon has been battling for years.

An Amazon spokesperson told WIRED: “Our expert investigators, attorneys, analysts, and other experts track brokers, piece together evidence about how they operate, and then take legal action against them. We are committed to maintaining trustworthy reviews on our store and this strategy of keeping scammers out is working.”

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