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Playcount

10 March, 2009

Today, I did something that I have been meaning to do for quite some time. And hopefully it will be an ongoing project (since it’s a lot of grunt work, it’ll be a perfect procrstination tool…)

Ever since I got iTunes, I have been enthralled with the play counter. I have a lot of playlists that are based on this gem of information, and I definitely cared about it enough to cheat it when I was listening to a song that I didn’t want people to know I had listened to. (Of course, now, if you stop a song in the last 10 seconds, it still counts as a play, so my plans have been foiled.)

But for about a year, I’ve noticed that the most-played song in my library has a count of 52, and 2/3 of my library (say, 10000 songs) has a playcount of 1 or 0. Now, this is partially because of playcounts being distorted by taking songs (and their metadata) from my old old iPod to put them onto my new computer. As a result, all but 2 songs in my Top 25 Most Played are from my old computer, and, honestly, I don’t really listen to them anymore. But, they still have a higher playcount, because I had that computer for about twice as long as this one. Regardless of the reason, the playcounts in my library were wildly disproportionate. Just like 95% of wealth being concentrated in the top 5%, or some similar statistic about energy consumption, most of my playcounts were concentrated in a small minority.

I finally decided to find out how much. I’m sure there’s a program that does this for you, but I just used good old copy-and-paste and Excel. And came up with the following:

My iTunes Playcounnts

This is the graph of the playcounts of my 500 most-played songs. As you can see, and as I sort of expected. It’s pretty logarithmic. I think that’s the right term. Anyway, it goes down drastically after the first, say, 25 songs, and then levels out. Now, keep in mind that this is only 1/30th of my library, so the steep drop at the beginning would be even steeper were I to put all of the playcounts here.

Partially as a result of this, I’ve decided to make more and better smart playlists, to try to counter this concentration effect. The first one is my Top 500 most played songs which did not come from my old computer, which, as far as I can see at the moment, is a much more accurate portrayal of the kind of stuff I listen to. My music tastes have apparently changed, but it’s still recorded in the computer. Also, incidentally, I realised the other day that a list of every single song I have played (or nearly) in the past two years is online, at last.fm. My computer automatically tells it what I’m listening to, and I don’t often think about this fact. But, if anyone ever wanted to know what I was listening to at, say, 3:04 PM on July 17th, 2007, I could tell them. [EDIT: Not actually true. Once you get a certain time away, it no longer gives exact times. However, it does still have the exact order of tracks, so in theory you could extrapolate, make a rough guess…]

Anyway, I found that interesting, and I just thought I should share.

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