Earlier quoted context omitted.
> Unless, they fix this and get more people to review honestly. I think they're going to run into a lot of problems. I don't airBnB, but a friend who does was recently berated by a host after leaving a 4-star review; that host claimed (don't know how true this is) that many hosts will refuse to rent to you again if you leave anything but a 5-star review. That and other things I've seen and heard about airBnB reviews…
The whole system of review curation that infests online markets is a problem waiting to be solved. Right now we basically have to parse reviews on the 4.4-5.0 scale because anything outside that is meaningless. It's amazing to go read a novel rated 3 stars (because it operates outside this loop) and find it transcendently good.
It isn't just online, and it isn't just a technology problem. I recently bought a car and the manufacturer sent me a survey about the process. The salesman made sure, numerous times, to let me know that I'd be getting said survey and that anything less than a 10 meant he failed and that there would be negative consequences for him. Since I was mostly happy with the process, I gave him all 10s, even though one or two areas I would have rated a little lower. He got his good review and it didn't really bother me, but the car company lost out on some potentially useful feedback.
Some of the problems - like different people having a tendency to rate on different scales, ratings coming from different factors, etc - seem pretty amenable to a ML approach to make reviews a lot more useful, though. I wonder if anyone outside of a handful of companies (Amazon, Yelp, AirBnB, Google, etc) has enough data to make it useful, though?