The High Tech Way Amazon Is Cracking Down on Fake Reviews

Amazon has continued its high-tech push into the future by deploying an artificially intelligent system to make sure customers see the most authentic reviews of a product.

Using machine learning, Amazon's algorithm will bump up the reviews that are deemed to be the most true to customers' experiences, giving an extra weight to newer reviews and reviews that have been voted by customers as being helpful.

"Amazon is enhancing the customer reviews system, adding a few changes we hope will help make product feedback even more useful to customers," Julie Law, an Amazon spokeswoman, told ABC News in an email. "The system will continue to learn which reviews are most helpful to customers and improve the experience over time."

Amazon filed a lawsuit in April against several websites the company accused of selling positive reviews to help bolster a product's rating on Amazon. If Amazon's new system works to enhance user experience, it could deal a significant blow to such practices.

Product reviews have been a cornerstone of Amazon's business for the past two decades. The new machine learning algorithm is being rolled out first in the United States and it's expected the changes will at first be subtle. If successful, the algorithm could usher in a new era for trust and the online shopping experience.

Shares of $AMZN opened strongly on NASDAQ this morning with the stock surging to a high of $439.24 this morning.



3 March 2017 14:53

Amazon (UK) aren't really interested in stopping it. They supposedly banned incentivised reviews last autumn, but it's still flooded by products from new Chinese companies making everything from kettles to earphones that reimburse their cohorts for 5 star glittering reviews. They're easy enough to spot, just look at a few of their profiles and you'll soon see not only the same old names reviewing the same products and giving everything 5 stars, but also such daftness as 'buying' 6 different umbrellas or cameras in a week, giving each an identical write up. 

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