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Crunching the Math On iTunes
markmcb writes "OmniNerd has posted an interesting article about the statistical math behind iTunes. The author makes some interesting observations concerning the same song playing twice in a row during party shuffle play, the impact that star ratings have on playback, and comparisons with plain old random play (star ratings not considered)." From the article: "To test the option's preference for 5-stars, I created a short playlist of six songs: one from each different star rating and a song left un-rated. The songs were from the same genre and artist and were changed to be only one second in duration. After resetting the play count to zero, I hit play and left my desk for the weekend. To satisfy a little more curiosity, I ran the same songs once more on a different weekend without selecting the option to play higher rated songs more often. Monday morning the play counts were as shown in Table 1."
Your decimals look more like the pricing model than the weights for playing songs..
.285 -- $299, iPod (full?) 20gb .238 -- $249, iPod mini 6gb .190 -- $199, iPod mini 4gb .143 -- $149, iPod shuffle 1gb .095 -- $99, iPod shuffle 512mb
5 star -
4 star -
3 star -
2 star -
1 star -
"Victory means exit strategy, and it's important for the President to explain to us what the exit strategy is." G.W.Bush
A friend of mine who worked at a radio station that played a very diverse range of music told me how they select music.
She said that research had shown that listeners would rate the same song higher if it followed other song of a similar genre. If they play songs of different genres randomly the listener does not enjoy the music as much.
So their tendency is to play "blocks" of music.
For example....
4 Classic Rock songs
3 Blues Songs
3 Folk songs
4 Female Rockers
3 Grunge
etc.
This is common knowledge in the radio world. I wonder if Apple has incorporated this type of logic into it's iTunes algorithms?
The radio station in question is WXPN and can be found under iTunes > Radio > Public > WXPN
points(0 stars)=1
points(1 stars)=3
points(2 stars)=4
points(3 stars)=5
points(4 stars)=6
points(5 stars)=7
probability(X stars) = points(X stars) / 26
This yields the following probabilities, listed along side the observed values from the article along with 95% condience intervals.
p(5 star)=.2692 [.270 +- .0038] .0036] .0033] .0031] .0027] .0016]
p(4 star)=.2308 [.230 +-
p(3 star)=.1923 [.189 +-
p(2 star)=.1538 [.154 +-
p(1 star)=.1154 [.118 +-
p(0 star)=.0385 [.039 +-
As you can see each computed probability falls within the 95% confidence interval, so there's a good chance this is the correct forumla.
Boy do I have too much time on my hands today.