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Ha, I made something very similar with the goal of mesmerizing passersby at a conference where we had a booth: http://www.a1k0n.net/spotify/artist-viz/

Used t-SNE on a vector clustering which came from LDA.

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Nice! I assume LDA was run on the lyrics?

Not at all... "documents" were the user's play history and "words" were artists. So if you played one artist twice and another artist once it'd be like a document that says "artist1 artist1 artist2". The assumption is that document topics are analogous to music genres, and each artist creates music within a small set of genres each user prefers music within a small set of genres.

Ah, that explains why the groupings are so good. That's cool, I hadn't thought about topic models outside of NLP before.

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