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

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.

Comments

Great algorithm - would implement!

[Anonymous Coward]

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.