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Comment by mashmac2 | Hacker News Reader

This would make a fascinating study of reliability - can you determine statistically if a product will be reliable based on rating distribution.

You could study Amazon, App Store ratings, etc. Cool insight!

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I wouldn't take any rating metric seriously unless it accounted for how long they've owned it. Plus there's the difference between "I've owned 12 lawnmowers and this one's pretty okay, only broke down after 1.5yrs, 3 stars" and "this is my first lawnmower, used it once, it's amazing, never going back to cutting my lawn with scissors, 5 stars". Plus niche sites sometimes have better reviews for the same products (newegg).

All that said, there is information to be harvested in some of these reviews.

Good point about niche sites and the length of ownership. I've noticed that a number of starts on products like top rated power supplies goes down after a year an a half or so. While you might be getting a newly released power supply with 500 reviews averaging closer to 5 stars, after 2 years, you will notice that same product with 1600 reviews averaging at below 4 stars, because owners probably came back and updated their reviews.

It would be interesting to see a trend line of change in sentiment about a products over time, using existing data.

It's been done, and I've seen it as a worked example in introduction to Bayesian stats pages, maybe some of which were posted on HN.

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