This is pretty neat, but the biggest problem for me is the case sensitivity; reddit itself doesn't use case sensitivity, so it's hard to remember the exact capitalization of a subreddit name.

Hi!

Great work. I guess my question is - do you use 'averaging' of word vectors or the Chinese Restaurant process - to get to sub reddit vectors. You describe the Chinese Restaurant process as a "more sophisticated method" that you "can" use, but in my experiments with word2vec and reddit (https://github.com/utunga/gensimred) I quickly discovered that simple averaging just does not work. Averaging has this awful 'revert to mean' thing that turns all the paragraph vectors into a sort of bland gray goo where they are all the same.

If you did use Chinese Restaurant process (I love that phrase - brings back memories of an occasion at a Dim Sum restaurant where this almost literally happened) it'd be great to see any source code you may feel like releasing ;_) ... well, it can't hurt to ask..

Very cool. Little tip: use "-funny" to get high-quality subs :)

Awesome seeing someone use the reddit dataset :)!

Wouldn't a w2v as a recommender for the user might have been better?

Taking user's comments/likes/subreddits as a feature.

neat, I'd suggest considering spaces as "+" i.e. "cats awww" should be the same as "cats+awww" I guess :)

Nice idea :), works well. Spotted a small typo in the examples:

pcmasterace+mac should be pcmasterrace+mac (missing an r)