[davidktr]

No, complete plays is simply their measure of user satisfaction. If I like a song, I usually listen to it until the end. If I do not like a song, I usually skip it after a few seconds.

How would you measure user satisfaction?

[mynameisvlad]

Said upthread, a much better metric would be use of the song outside of the generated playlist. Added to other playlists, added to library, listened to again hours or days later of your own accord, etc. Basically, in some way tied to a user action rather than the absence of one.

I’m fairly open to music, I’ll likely listen to a song once if it’s on a playlist. But that doesn’t mean I liked the song, only that I gave it a shot. It certainly means I liked it more than the song I just skipped, sure, but it also doesn’t mean I necessarily want to hear it again.

[d0gbread]

On these AI generated playlists I'll actually skip songs even if I like them because I'm just cruising through the list, then might go and save a full album from the band to check out later, in full. So the selected behavior is really not representative in my case.

[p1esk]

I'll actually skip songs even if I like them

So you don’t add them to your library?

[neura]

Not when it's recommending something it _should_ already know I like (and probably why it added it to the list). Also, sometimes, I may like something, but not add it to my personal list. Since there's no way to rate a song, I use likes only for songs I really like.

I think the real point to be made here is that this is part of the inner workings of the system, that most users of the system are unaware of. Hell, this article and the ensuing discussions do not leave it completely clear how much of the system works. Like, I despise that when I create a new playlist with a name, it recommends a bunch of tracks based on the name of the playlist. Sometimes that'll be tracks with words in the name of the playlist in their name or some other odd metric, like it'll add songs from an artist that has a song that happens to be the name of the playlist. If you don't puzzle this out for yourself, you're possibly creating a very UN-optimized playlist for yourself.

[jjj123]

I think complete plays is a pretty fair metric, though it hurts 45 minute long epics or Dj sets or w/e.

The bigger issue I have is with “number of times played.” I listen to some comfort-food music over and over again, but the most rewarding music I listen to is challenging in some way and maybe isn’t something I listen to over and over.

Basically, Spotify’s metrics aren’t my metrics.

[neura]

Complete plays is a fair metric, if it doesn't take into consideration related traits like when I love a particular remix of a song that is very different than the original, the system decides that I loved the original song and is now going to recommend songs similar to or liked by other users of the system that liked that original song.

This is another place where Pandora really set themselves apart, the Music Genome Project. Any given track that went through curation has a (possibly very) large set of attributes assigned to it. This song you liked, it has a heavy bass-line, noticeable amount of shuffle, light drums, syncopated rhythms, etc. That's far better (to me) than "you might like other songs by this artist" or "other listeners of this artist also listen to", where the last one gets really sketchy when there's not a lot of listeners for the artist.

I'm also curious how it treats listening to a track on a Spotify station that is mixed, where they transition in to and out of the track late or early, so you won't hear the full track, does that still count?

Heck, sometimes I'll get almost to the end of the track and skip to the next just because the track has a long tail and I want to get to something that has more energy, not the dwindling remains of the rhythm or some soft piano fade out at the end of a 130 BPM track that had a lot of energy throughout most of it.

If they're going to make all of these sometimes seemingly arbitrary judgements of whether or not I like something based on these weird things like "there's a common English word in the playlist title that also shows up in all these song titles we're going to recommend to you", at least a list or chart of how it works somewhere would be nice, so I can make more effective use of the system.