sayit

I think for smaller subreddit's there's not as much data, so results are more noise. Apparently Jaccard similarity was used, except for the really big subreddits: https://github.com/anvaka/sayit Unrelated, but had to say it somewhere in this discussion: Thanks @anvaka for your open source graph libs! Way more performant than anything else I've tried.

I used my own metric that is based on jaccard similarity. Which in turn is based on "users who posted to X also posted to Y" metric. That said, there are a few subreddits that are too popular and similarity results were too saturated (/r/videos, /r/funny, etc.) so I did a manual override by looking into most commonly mentioned other subreddits, and sometimes into `about` blurb of subreddit). Please don't consider these recommendation as source of truth! It's just a fun way to discover other subreddits :). I'm also very open to change this metric to something else - please let me know if you have any recommendations! [1]: https://github.com/anvaka/sayit#the-data - describes the data, indexing scripts are here: https://github.com/anvaka/sayit/tree/master/scripts [2]: Manual overrides can be found here https://github.com/anvaka/sayit-data#sa

There are such projects, and in fact - I mention two of them. If you want to obtain data, Related subreddits shared it (150GB or so): https://github.com/anvaka/sayit