One of the innovations of online stores is the ability for users to rate what they like and then for other users to base decisions or comment on those previous ratings. A site like Amazon.com is amazing in this regard; within a few minutes, a reader can get a much better idea about a product.

But statistics from Netflix, another site that allows user reviews, indicate that many users don’t rate anything while there is a small percentage of people who might be called “mega-reviewers”:

About a tenth of one percent (0.07%) of Netflix users — more than 10,000 people —  have rated more than 20,000 items. And a full one percent, or nearly 150,000 Netflixers, have rated more than 5,000 movies. By contrast, only 60 percent of Netflix users rate any movies at all, and the typical person only gives out 200 starred grades.

This rating pattern might fit a Poisson or a negative binomial regression where many people rate none or very few movies while there is a smaller percentage who rate a lot. (A useful statistic in helping to figure out the shape of the curve: while there is 40% that doesn’t rate anything, of the 60 percent who rate any movies at all, what is that median?)

The Atlantic talks to two of mega-reviewers who seem to motivated by seeing what the system would recommend to them after having all of their input. Interestingly, they suggest Netflix still recommends movies to them that they don’t like after watching them.