I’m puzzled by the shopping lists ranking views. For example, at newegg.com I searched for a product, got the list, then I set the display to order by “Best Rating”. Now I get a bunch of stuff and the top two items are
Doesn’t that seem odd? The first item is listed first, yet it only has two reviews, whereas the second item has a lot more reviews. True, the first item has no negative reviews. Is that why it’s listed first? Doesn’t sound correct to me.
I searched for an explanation on the site, but did not find one. Yet, I don’t see an alternative. My gut feeling is that the second one should be first. It doesn’t have the best rating score, but it has the best rating responses so should be more accurate. Isn’t this covered in Statistics 101?
I’m sure there are nice algorithms or frameworks to make this more useful. Then again, maybe not. I’ve searched and I don’t find any definitive answers. Yet, there should be. How do people rate user ratings? Gut feel only?
Another example, I searched for a book on Amazon, the new Lee Child’s “A Wanted Man”. The user ratings were:
|1 star||2 star||3 star||4 star||5 star|
Just based on the ratings score, without reading the feedback, is this a “good” book? Note, here are a few statistics measures, though be wary, my statistics 101 was not recent:
Using the SurveyMonkey computation we get a Rating Average of 3.5. This is a 4 Star rating. Seems the Survey Monkey approach is to the use the vote count of each each cardinal star as a weight. This gives an expected value computation.
Here are a few references on this that I hope to read one day:
- A comparison of Fuzzy, Bayesian and Weighted Average formulations of an in-stream habitat suitability model.
- How Not To Sort By Average Rating
- The Social Network Ranking is Wrong
- How Reddit ranking algorithms work
- What is the Rating Average and how is it calculated
- Algorithm for Rating Objects Based on Amount of Votes and 5 Star Rating
- Rating Scale
- A Bayesian view of Amazon Resellers
- Bayesian average
- Brewing a Better Rating System
- DISCUSSION OF FUNCTIONAL DESIGN OPTIONS FOR
ONLINE RATING SYSTEMS: A STATE-OF-THE-ART ANALYSIS
- Collaborative filtering