But the link-relationship methodology is interesting (similar to something like PageRank through backlinks).
But it's not the methodology I'd have initially gravitated towards.
My first instinct would be relations based on subscription overlap. This seems like it should group commonalities based on the user interests. This may also have alleviated some of the SPAM issues.
Though it would have been interesting to see both approaches merged together.
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.
We may have tried other methodologies as well, I honestly don't remember. I feel like subscription overlap was something we at least talked about, but maybe not.
But the link-relationship methodology is interesting (similar to something like PageRank through backlinks).
But it's not the methodology I'd have initially gravitated towards.
My first instinct would be relations based on subscription overlap. This seems like it should group commonalities based on the user interests. This may also have alleviated some of the SPAM issues.
Though it would have been interesting to see both approaches merged together.