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Posted on June 19, 2009
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This is an excellent article on the possibility of using data generated by digital music management systems to understand the way in which people listen to music.  Distressingly, it shows that there are a lot of people who really, really like Metal, which is how I discovered, the extraordinary video of the guitarists from The Children of Bodom recreatting The allegro movement form Vivaldi’s Four Seasons on their axes dudes – awesome! But that’s down the bottom of the page, first you have read the article and have a think about heavy shit before you watch cool dudes with really long hair play guitar very fucking fast…

One of the ways that Music 2.0 has changed how we think about music is that there is so much interesting data available about how people are listening to music.  Sites like Last.fm automatically track all sorts of interesting data that just was not available before.  Forty years ago, a music label like Capitol would know how many copies the album  Abbey Road sold in the U.S., but the label wouldn’t know how many times people actually listened to the album.  Today, however, our iPods and desktop music players keep careful track of how many times we play each song,  album and artist – giving us a whole new way to look at  an artist.  If you go to Last.fm you can see that The Beatles have over  1.75 million listeners and 168 million plays.  It makes it easy for us to see how popular the Beatles are compared to another band (the monkees, for instance have 2.5m plays and 285K listeners).

With all of this new data available, there are some new ways we can look at artists.  Instead of just looking at artists in terms of popularity and sales rank,  I think it is interesting to see which artists generate the most passionate listeners.  These are artists that dominate the playlists of their fans.   I think this ‘passion index’ may be an interesting metric to use to help people explore for and discovery music.  Artists that attract passionate fans may be longer lived and worth  a listeners investment in time and money.

How can we calculate a passion index?   There are probably a number of indicators:  the number of edits to the bands wikipedia page,  the average distance a fan travels to attend a show by the artist, the number of fan sites for an artist.  All of these may be a bit difficult to collect, especially for a large set of artists.  One  simple passion metric is just  the average number of artist plays per listener.  Presumably if an artist’s listeners are playing an artist’s songs more than average they are more passionate about the artist.   One thing that I like about this approach to the passion index is that it is extremely easy to calculate – just divide the total artist plays by the total number of artist listeners and you have the passion index.   Yes, there are many confounding factors – for instance,  artists with longer songs are penalized – still I think it is a pretty good measure.

I calculated the passion index for a large collection of artists.  I started with about a million artists (it is really nice to have all this data at the Echo Nest;), and filtered these down to the 50K most popular artists.  I plotted the number of artist plays vs. the number of artist listeners for each of the 50 K listeners.    The plot shows that most artists fall into the central band (normal passion), but some (the green points) are high passion artists and some (the blue points) are low passion artists. more

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