[jules]

That formula will give an item a higher score the more down votes it gets. A better approach is

score = (pos + a) / (tot + b).

Where a<b, e.g. a=1, b=2.

See this post why that formula follows from Bayesian reasoning: http://julesjacobs.github.io/2015/08/17/bayesian-scoring-of-...

[tabtab]

I'm not sure what you mean in the 1st sentence. Example? The problem with the 2 weights is that it's 2 values that have to be given, and for large quantities neither makes much difference. It's why I used log().

[jules]

The log(total) term increases without bound whereas the pos/tot term is at most 1, so in the limit of a lot of votes you will beat an item with fewer votes even if all your votes are downvotes.

That there are two configurable parameters is a good thing. One parameter controls how much of a penalty you get for having few votes, the other controls how many votes count as "few".