Fake reviews and content
moderation
Fake or abusive reviews and user-generated content pose a growing concern
to today's organizations, with customers increasingly relying on online reviews
to help them make purchasing decisions. Fake reviews or content posts, like
someone posting a fake review to an online marketplace, can unfairly cause
products to develop negative reputations, detract from overall ratings and
rankings, and boost the visibility of subpar services or content. Abusive reviews,
such as those containing profanity or racist, sexist, or threatening language, can
anger users and cause them to defect from a platform or turn to a competitor—
especially if they determine that this behavior is not well policed.
AWS machine learning solutions for fraud detection can be used to help
automate screening for fake and abusive reviews. This can allow your customer
service teams to save time, freeing them from wading through mountains of
alerts, many of which may be false positives. Amazon Rekognition, Amazon
Transcribe, and Amazon Comprehend can be used to streamline and automate
your image and video moderation workflows. By catching fake or abusive
content earlier and more accurately, you can better protect your reputation
and your customers.
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