That would not produce anything close to this. Is the goal to find similar subreddits, or find other non-similar subreddits the person may like? The map by OP is grouped by categories, which is quite a bit different than just interest. Even for recommendation system, I don't think it quite works here due to how extremely wide reddit is. Something like Steam or Spotify can use it, but reddit has everything from porn to cities to games. Just because I love Portal and I'm from Vancouver doesn't mean someone else who likes Portal will care about Vancouver, or vice versa.
Yes, but the majority of /r/Steam users are not subscribed to /r/Vancouver (or whatever the Vancouver subreddit is). I'd wager a guess there is a much more significant overlap with related subreddits such as /r/pcgaming.
I think this is how Last.fm works (and it works quite well!)
The weirdness in disparate interests is smoothed out by having a large sample size.
I'm trying to find details of the algorithm. In the meantime, here's an interview with the inventor of AudioScrobbler, which merged with Last.fm to provide its recommendations system: https://www.wired.com/2012/11/richard-jones-scrobbling
Well, have you read the methodology used by this map?
> Each dot is a subreddit. Two dots within the same cluster are usually close to each other if multiple users frequently leave comments on both subreddits.
So it's not exactly about subscribers, but it's the same idea, which proves your refutation wrong.
