Since talking with Gabriel at MusicStrands the other day, I've been thinking more about how we share our musical tastes with others. I was making the point to him that there should be a way to quickly relate the type of music you're interested in without forcing people to wade through months of listening data like the current social music services require. For example, you can see that my top two artists at Last.fm are Bob Marley and Mozart based on frequency of plays, but that doesn't mean that my top two genres are Reggae and Classical. (I wouldn't place those as my top two if someone asked me.) You have to wade through the entire list to see that I also like classic rock, indie rock, electronic music, and lots of other genres.
What I was trying to say to Gabriel, but couldn't quite articulate, is that there should be a Myers-Briggs
style scoring system for musical taste. When I see that someone is an ENFP, I have one instant measure of their personality. If you could do the same for music, you'd have a way to instantly relate your musical interests. I'm not sure what the criteria would be—maybe I'm an ISAE (indie structured ambient electronic), or MECR (mainstream eclectic classic rock). And this would go hand in hand with a service like MusicStrands because they can analyze the last 1,000 songs I actually listened to. With the score in hand, I could paste it into the dozen or so social network sites I belong to, giving people a more nuanced look at my preferences than my top 5 bands or something.
The iTunes Signature Maker
is one stab at this concept. This application wades through your iTunes collection and creates a short audio signature based on the music it finds. When listening to others' signatures I guess you could listen for electronica vs. distorted guitars, but it doesn't really give you a sense of music preference. This is more of a fun hack than a useful way to share your musical identity. It'd be much more accurate to analyze what you're actually listening to, and then do a bit of categorization based on meta info about those tracks.