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I have a community based website and I am receiving some complains about the way I make the rankings of content.

The focus of the platform is user-generated reviews. The problem is that I use an arithmetic average, and if a product have 1 five star review will rank higher than a product with 100 4 stars reviews.

So this is a problem, since the top of the rank is products with only one or two reviews. The easy solution is just remove products with less than X reviews. Although I am not sure how other platforms are dealing with this case scenario. Any idea?

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The key concept here is that more votes should increase your confidence of the ranking. There are a lot of rather complicated forumlas you can use but the general principle was explained by HeapUnderflow on forum.codidact.org:

I’ll summarize what you would have seen. The Wilson score is a prediction of how likely a vote is to be an upvote, based on the votes so far, so it comes out as number between 0 and 1, exclusive. The ratio of upvotes to downvotes is the most important factor, but it will give a little higher score for 20:10 than 10:5 because more data means more confidence.

Consensus at the Codidact forum was that a simple formula for up/down-voting that gives more confidence for more votes is

(upvotes + 2) / (upvotes + downvotes + 4)

But the Wilson score is only designed for up/down rating. I've found a couple of questions on the SE network concerning star ratings, and you might be able to search for more. Sorry that I can't give you more specific advice.

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