Why the 5 Star Rating System Isn't Suited to Local Reviews (thebuzz.at)
Yelp (or Qype/Citysearch/TrustedPlaces/Tipped etc.) are not deliberately misleading their users, but fundamentally they’re all broken, the foundations on which they’re built are unsound.
24 comments
[ 0.23 ms ] story [ 46.6 ms ] threadHere's a screenshot:
http://img.skitch.com/20090504-n2jsr44y1py38pbd5wgcqs5uyn.pn...
One major problem is the need to click through to the detail page to see these charts, this doesn't lend itself to easy decision making on the fly. However, the real issue is that even when you do click through, it doesn't show probably another important metric by which to judge: volume of votes over time. If you were to add that into the equation and suddenly the user has 3 charts per venue to interrogate to establish the reliability of the initial score out of 5.
I think that's a reasonably big ask for someone who just wants to know where's to get a decent Kung Pao chicken around here.
When flipping channels looking at movies that are on, the star rating system is largely worthless because 1) it was most likely done by some paid movie buff who has inherently different motivations and likes/dislikes than I do and 2) there is no explanation as to the reasoning why a rating was given. It's all subjective measurements, and it can't be objective. The whole point of rating systems is opinion. It's just like asking a friend if a place is worth going.
Often times, the use case is "find something good with a minimal amount of hassle". This comes down to things like "places people liked that are within a mile of where I am right now". I have five minutes to make a decision on this, the single data point of a rating scale helps me make the decision quickly and (perceptually) accurately (it may not actually be accurate, but I feel like I'm making a good decision). These sites are also designed for repeat users and users being contributors. You learn the way other people have rated things on the site over time and are more able to decide for yourself what a "1 star" means vs a "5 star" means given the context.
I think a larger problem is getting people to want to expend the effort to provide a review of a place that they aren't extremely excited about (either positively or negatively). I know I don't bother to review places I had a so-so experience at, but if I had excellent service or really bad service, I make it a point to rate them. In some way, this skews the results, but is most likely isn't that big of a deal.
I don't know what the OP has in store for his next posting, but if it's truly revolutionary, he should be starting his own competing review service.
What I'm proposing isn't new or revolutionary - it's simply that we need a more honest appraisal system - something that everyone can understand not just think they understand because it's presented in a familiar and reassuring format (5 stars).
Discussion of the Netflix Prize is a good place to mine data on the accuracy of rating systems and improve them.
And what makes it look like an opinion system could be honest? I said an opinion system could be made more honest. To be clear, I'm not suggesting that the people voting are misrepresenting their position (the users are dishonest) merely that the 5 star rating system that purports to tell us something of value, doesn't (the system is dishonest).
Honesty comes from simplicity and it's my opinion that aligning online recommendations systems more closely with "real world" models is not only purer (in that we'll have a greater innate understanding) but probably more accurate and more helpful as a decision making aid.
As for the Netflix Prize, I can't help feeling that it's not much more than asking how many angels can dance on the head of a pin?
Maybe it's just me, but I'd prefer a probability system such as up and down votes. If I see a restaurant has 100 "likes" and 10 "dislikes" it's probable that I'll also enjoy the place (given the fact I already know they're serving food and drinks I would normally enjoy).
I'd suggest that the score be rendered as a Sparkline of aggregate-score-over-time, with a surrounding colored field, the width of which is the deviation for that aggregate sample point. Thus, you could see whether a five-star restaurant used to be a three-star at a glance, and see how many people disagree with the current rating with a simple visual geometric comparison.
Why? Because even Yelp understands the "The man who drowned in the river whose average depth was 6 inches" problem, which is exactly why they offer both a histogram view of ratings, and an average-over-time graph. I frequently use both of those tools.
Now don't get me wrong there are all kinds of problems with 1-5 rating schemes, and there are probably better schemes out there. But what Yelp does is as good as any I've seen towards combatting the problem, which is why I enjoy using it.
As someone that took 4 semesters of business statistics in college, my personal favorite alternative scheme is paired-comparison, or even better yet, the related (and newer) MaxDiff algorithm [http://en.wikipedia.org/wiki/MaxDiff]. The only problem with these schemes are that they require much more user input which frankly is a lot to ask for on a site like Yelp.
But the point is that while the 5-star system initially looks and feels like it's offering some real data with which to evaluate a bar/restaurant, the reality is that the data need advanced interpretation to come even close to being meaningful not to mind useful.
There's probably not a perfect system out there but I'm pretty sure that other models would be more "honest" at least.
In fact, I think this is exactly where the complication arises from. I agree that that is probably a close approximation of the question one would like to have answered, but asking people to give a rating out of 5 stars certainly doesn't ask it. Not only that but it actually muddies the water somewhat when aggregate data is spat out as an answer.
I also don't see how any of this leads to less or more "honesty" in the ratings.
The best rating systems I've seen looked something like this:
orhttp://www.evanmiller.org/how-not-to-sort-by-average-rating....
Not sure how sound my math is, but it seems to produce the desired results.