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>items with the most reviews are going to rise to the top Yes and no. Anything with a larger N is going to make for greater confidence in the rating. But tha
by Perceval 17y ago
>items with the most reviews are going to rise to the top
Yes and no. Anything with a larger N is going to make for greater confidence in the rating. But that rating still depends on the number of positive and negative reviews. So if a product has a large number of ratings, but they are 50/50 positive and negative, then it's not going to rise to the top simply because it has the most reviews. The algorithm would presumably be very confident about placing it in the middle of the pack.
- Automatt-2 17y ago>So if a product has a large number of ratings, but they are 50/50 positive and negative, then it's not going to rise to the top simply because it has the most reviews. What I'm saying is that it will rise to the top because even though only 50% of the ratings are positive, it will have many many more positive ratings than the nearest next item. That 2nd item may have a much higher percentage of positive ratings, but a much lower number of total ratings.
- DougBTX 17y agoIt seems to work as described in the article: require 'rubygems' require 'statistics2' def ci_lower_bound(pos, n, power) if n == 0 return 0 end z = Statistics2.pnormaldist(1-power/2) phat = 1.0*pos/n (phat + z*z/(2*n) - z * Math.sqrt((phat*(1-phat)+z*z/(4*n))/n))/(1+z*z/n) end puts ci_lower_bound(60, 100, 0.10) # => 0.517809505446319 puts ci_lower_bound(500, 1000, 0.10) # => 0.474027691168875 puts ci_lower_bound(50, 100, 0.10) # => 0.418847795168265 The top ranked result has 60 positives out of 100, and beats 500 out of 1000 - almost 10 times as many positive votes.