iTunes: Just how random is random?

Say You, Say What?
Using Excel, we collated the results and counted the number of times that each song and artist appeared in the playlists iTunes had generated.

All things being equal (and random), one would expect that a field of 1300 song slots would provide enough opportunities for each of the 56 artists to be equally represented. However, this was not the case. In fact, even though each specifically chosen had five songs in the library, there was a large discrepancy between the most popular and least popular artists.

Top 10 artists

Lionel Richie (Universal) proved to be iTunes' most popular artist, appearing 59 times all told, for an average of 1.475 times per possible playlist (or TPP, an objective measure reflecting the fact that iTunes-purchased songs were available to iTunes during creation of 40 playlists while CD-ripped songs could only have appeared on 20 playlists).

Red Hot Chili Peppers and The Veronicas tied for second place (55 times / 1.375 TPP) with Keane and Robbie Williams (53/1.325 TPP), Eskimo Joe (52/1.3 TPP), Good Charlotte (51/1.275 TPP) and Grinspoon (50/1.25) all appearing at least 50 times in our playlists. Looking further down the list, however, a curious trend appeared. Artists whose five songs were bought from iTunes were consistently more likely to appear on the random playlists than those whose songs were ripped from CD. Each of the top 15 artists, by number of songs played and songs per playlist, was bought from iTunes; those ripped from CD were far less likely to rate.

Songs by Def Leppard, the most frequently-played artist from CD, were chosen 24 times in 20 possible playlists for a TPP of 1.2 -- but the rate of selection for other CD artists quickly dropped off: Bon Jovi (21/2 TPP), Creed (20/1 TPP), and Gloria Estefan (18/0.9 TPP) were all slightly ahead of Andrew Lloyd Webber, the Bee Gees, Dido, Erasure, Jackson Browne, Maroon 5 and Mötley Crüe, all of which were played 17 times for a TPP of 0.85.

The least frequently played artists were all those whose songs were taken from CD, with the bottom of the rung inhabited by Kate Bush (12/0.6 TPP), Anderson Bruford Wakeman Howe (11/0.55 TPP), and Christina Aguilera and Oasis (10/0.5 TPP).

When the artists with just one song were factored in, things got even more interesting. Smack That -- a current hit by Akon and Eminem -- was played 17 times, which was the mean for the artists with five songs in the iTunes Library. Its TPP was 0.425, a frequency that translates to 2.125 if treated as though there were five copies of the song (we'll call that ratio TPP5). In other words, we were 1.44 times as likely to hear Smack That than any song by Lionel Richie, even though Lionel Richie had five songs in the iTunes Library.

Also played proportionally more frequently than five-song artists were Gwen Stefani's The Sweet Escape and Hinder's Lips Of An Angel (14/1.75 TPP5), Justin Timberlake's What Goes Around/Comes Around (13/1.625 TPP5), and Daughtry's It's Not Over (12/1.5 TPP5). Beyoncé's Irreplaceable, Fall Out Boy's This Ain't A Scene, It's An Arms Race, Gym Class Heroes' Cupid's Chokehold, Nelly Furtado's Say It Right (11/1.375 TPP5) all had as many playlist appearances as songs from the Red Hot Chili Peppers and The Veronicas -- even though the latter artists should presumably have been five times more common.



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KarlM1 posted a comment   
Hong Kong

This is a great study, but leaves out the P value. You don't actually expect perfect balance. If the random generator were perfectly random, what's the probability that you'd get the distribution you observed?

I'm all in favor of independent music (especially Creative Commons-licensed music), but skewed random playlist generation isn't necessarily the result of some sinister intentional conspiracy against smaller/independent labels.

I imagine if I were tasked with coding up something like this, I'd start out with some simple enjoyability model and keep track of when a user skipped songs in order to (over time) build first- and second-order Markov models of a user's listening habits. Popularity of purchases from iTunes is one of the obvious simple enjoyability models I'd look at for the "average user". (Yes, there is no such thing as an average user, but sometimes it's a useful fiction.)

 

weffing posted a comment   
United Kingdom

I agree that the data here is sparse. Try the same thing again with much more material and more randomness from your side. Another interesting variable could be "how long a particular song/group of songs has/have resided in the itunes library"


Personally i would like a setting that would limit every song in a random list to only one spot, forcing every song in a playlist/library to be played. I have a feeling itunes used to work that way before it became a "store".

 

DukeOfC posted a comment   

Humans looking at bar graphs and commenting on how they should have close to the average is not statistical analysis. Complete your study by running an ANOVA test.

 

anttumad posted a comment   
Egypt

sorry. It is not uncomplete.

Great job!

 

anttumad posted a comment   
Egypt

The article is uncomplete. Isn't it?

 

Unter09 posted a comment   
United States

Where can I buy the album with John Denver & The Muppets?

 

Johanna posted a comment   

I notice songs with similar beat come usually in a row.
In every 3 or 4 songs, the type of beat changes...

 

Steve posted a comment   

Absolutetly no statistical analysis was done here, ever heard of a normal distribution?

 

MattyRob posted a comment   

One day my entire music library was on shuffle and it came to a song by Florence + The Machine. The TWO songs after that were also by Florence + The Machine, the same album. There are approximately 650 songs on my iTunes so I thought it was odd that three songs by the same artist/same album would play in a row! I want to know the odds!

 

Thomas posted a comment   

Having used this for quite a while, I've noticed an annoying trend that only has shown up in the recent version: iTunes loves to pick songs that were just playing earlier. If I'm listening to a song outside of shuffle, you can bet it shows up shortly in the shuffle list. When a song shows up in shuffle, there's a good chance it shows up again later, sometimes even happening a third time. The other night, I took a peek at the "last played" times for the next batch of songs, and nearly six in a row had been listened to the previous time.
It also likes to pick multiple tracks from the same album, such as picking three songs from the same album in a row, with a couple more coming before and after. I end up skipping a good number of shuffled songs, only because I was just listening to it earlier. Oy.


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