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New Algorithm Recognizes Both Good and Bad Fake Reviews (thestack.com)

Posted by samzenpus on from the do-you-really-like-it? dept.

An anonymous reader writes: Researchers from the university of Sao Paolo have developed an algorithm able to identify both good and bad online reviews in the massive daily chatter of millions of peer-community posts, and in lateral mendacities at social network sites such as Google+ and Facebook reposts and 'likes'. Two of the datasets tested in the research were from Amazon, which has a vested interest in restoring the reputation of its community reviews, and has recently taken action on the matter.

3 of 59 comments (clear)

  1. Great algorithm - would implement! by Anonymous Coward · · Score: 5, Funny

    While I have spent a lot of time studying algorithms, I still like to look for new algorithms from time to time. This algorithm is definitely one of the better algorithms I have come across in my life.

    When I first started studying the algorithm, I wasn't sure whether it was for me. However, after the first few pages, the algorithm began to grab my attention, and soon I was finding its average and worst case complexity and formally proving the correctness of several subroutines. I was astounded to find that it was at least as good as all the other algorithms I'd found over my twenty years' experience.

    While I wouldn't recommend this algorithm to a beginner without guidance, the journeyman will soon find themselves reaching master by applying this algorithm. The master cannot fail to learn something new from it.

  2. That's easy by Anonymous Coward · · Score: 2, Funny

    Just return true all the time. Sure there will be a few false positives but not enough to throw the results off by much.

  3. My Review of this article by Anonymous Coward · · Score: 2, Funny

    It combines orgasmic whitefish essences and loud mustard overtones with a stale nacho aftertaste.