Is it so difficult? Amazon already has the number of helpful vs unhelpful votes for each review. They could start with that voting data, and then use metadata

Is it so difficult? Amazon already has the number of helpful vs unhelpful votes for each review. They could start with that voting data, and then use metadata (geoip, account usage/posting timing, client fingerprinting) to create quality metrics for each user. They could even have separate trustworthiness ratings per product category (a good book reviewer might not be so good at rating appliances). From there, they'd have a rough idea of which reviews are real and fake, and they could start training a NN on the text. Figuring out when sellers are complicit, and when it's competitor sabotage, is more difficult, but Amazon has a ton of data about sellers and reviewers and buyers and the social/commercial graph connecting them. Amazon doesn't appear to be working on solving simpler problems, such as incorrect product/book comingling. Therefore, I have trouble giving them the benefit of the doubt that they're working on hard problems like addressing fraudulent ratings/sellers.