Spotify’s Discover Weekly: How machine learning finds new music

Post by anidesh1512 » Wed, Oct 11, 2017, 4:44 PM UTC

ar-nelson wrote: post #210

hammock wrote: post #203

Earlier quoted context omitted.

Don't you have Daily Mixes? These are smart playlists created by Spotify organized roughly into genres, and you have can up to six - depending on how diverse your listening habits are. Right now I have: 1 Electronic, 2 Pop, 3 R&B, 4 Indie, 5 Rap, 6 Country/Americana Note they aren't named like this, I did that. Spotify identifies them only by a number and a few of the artists contained within. You can find them in th…

These solve the problem somewhat, but, in my experience, they only play songs I've already listened to. So listening to songs outside the genres I want recommendations for will still ruin Discover Weekly's usefulness as a discovery system. I used to love Discover Weekly, and found a lot of great music through it, but it's gotten less useful over time. A few things that would improve it: • Multiple Discover playlists…

Post by Gargoyle » Wed, Oct 11, 2017, 4:52 PM UTC

Post by shostack » Wed, Oct 11, 2017, 5:02 PM UTC

Cthulhu_ wrote: post #70

iddqd wrote: post #58

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I used to listen exclusively to Discover Weekly for a while. One week a finish rap song made it to the list, and I skipped past it every time it came on. Next week there was 2 finish rap songs. Then 5. Eventually half of my discovery list was finish rap, something I have no interest of. Canceled my subscription shortly after. Their algorithms are feeding themselves. I wish they had a dislike button so I could at leas…

They do have a dislike button though, the thumbs down icon next to the play controls (on the desktop version of Spotify).

Post by nkozyra » Wed, Oct 11, 2017, 5:04 PM UTC

anjc wrote: post #168

nkozyra wrote: post #110

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I really don't understand why collaborative filtering isn't the sole approach. It's basically exactly what you want if you have that volume of data.

Relying on collaborative filtering (using play counts, as Spotify do) can lead to non-diverse and non-serendipitous recommendation. If I like Abbey Road then a typical collaborative filtering scheme might tell me I like Sgt Pepper's and Let it Be. Excellent recommendation, but useless if I'm already familiar with the band and the genre. There might be an unknown Japanese band that'd suit my tastes perfectly and I'd n…

Post by marcinx27 » Wed, Oct 11, 2017, 5:15 PM UTC

dvlsg wrote: post #209

nobleach wrote: post #172

I find that my music tastes can vary too much for Spotify. While working, I mostly listen to Electronic music. But I can also take a hard right turn and listen to Hall and Oates... or Fleetwood Mac, or Steely Dan. Then some form of 80's throwback. But as far as recommendations go, I really only want to expand in that first genre of Electronic Music. I don't want Jethro Tull to be recommended to me. My feed used to be…

You could try this tool from hate5six: http://hate5six.com/sage - historically, they've only worked with hardcore / metal music, but this appears to be a new tool which expanded out to 200k artists across all types. I managed to find 3 folk artists which I am loving, and had never heard of from either Google or spotify. Curious if it is broad enough to work for your taste in music. (not affiliated with them in any wa…