Re:Yelp Is Exploring a Sale
by nerfhammer on Friday May 08, 2015 @12:51PM
(#9512714)
Work has been done on this. Apparently you can detect fake reviews to some degree using text features alone:
I'm pretty sure the review filter (that everyone loves to hate) works this way.
Re:Yelp Is Exploring a Sale
by incongruity on Thursday May 07, 2015 @09:17PM
(#9509484)
I've assumed it's something like that - but it shouldn't be too hard for them to be a little more forthcoming to explain their methodology a little bit without compromising the value of it.
- Age of account
- Account engagement (patterns matter too)
- Check-ins via a mobile device at the business
- Check-ins at other near-by businesses (patterns matter too)
- Partner with a Credit Card company to offer Yelp-reward bucks to encourage reviews, track usage and validate reviews (and reviewers) [Use this to feed into the engagement score, above]
- Partner with OpenTable (they do this) & prompt reviews after attendance (they do this) – weight these reviews more heavily. [Use this to feed into the engagement score, above]
- Let me actually identify myself to Yelp or to the world (or to just business owners, ONLY if I want to [Use this to feed into the engagement score, above]
- Reviews of similar businesses (e.g.: I like thai food) -- patterns matter here. Do I rate all competitors poorly, etc? Did I post all reviews in one day, etc?
- Do my reviews vary significantly in a systematic way from others in a category? (This shouldn't be enough on its own, but variance might mean something)
- Do I post photos of the place? (Factor into engagement score, above -- but if it's only for one business, it might be a flag)
etc., etc.
Really – a statistical model shouldn't be that hard to do -- maybe processor intensive, but hard? It doesn't feel hard, given all the data they're sitting on...