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The lie of music discovery algorithms

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Re: The lie of music discovery algorithms

#41

Post by Tostino »

khafra wrote: post #40
aljgz wrote: post #17

In the age of internet, engagement optimization and recommendation algorithms create a new way that we are affected by the behaviour of others. That annoying dark pattern on a piece of software you use? Because there are people who fall to it, clicking on an ad or "engaging" more. That stupid show that keeps being recommended to you? Because a lot of people just sit on the couch, watching something on the list that d…

If you have any taste at all other than "maximally dissimilar to anything I have liked before," there should be a feature that predicts songs you would like. If your taste is exactly "maximally dissimilar to anything I have liked before," that's actually pretty easy to calculate from the embeddings as well.

It didn't sound like op wanted maximally dissimilar from what they've liked before, but instead maximally dissimilar from what they've listened to recently.

Re: The lie of music discovery algorithms

#42

Post by linuxftw »

I don't listen to any auto-play streaming service. It always devolves into the latest pop music that I don't care for.

If you like old-school metal, here's some great youtube channels (no affiliation to myself):

https://www.youtube.com/channel/UCCGbKiCJjph8Grazqmo7z4w https://www.youtube.com/channel/UCD5Ny_jQ8cs9JXVPWXg9iNw

Support these small bands.

Re: The lie of music discovery algorithms

#43

Post by loudmax »

cainxinth wrote: post #36

I’ve used everything, new and old media: Spotify, Napster, CMJ, pitchfork, bandcamp, allmusic, mojo, SoundCloud, beatport, last.fm, Apple Music… Nothing beats that one friend who used to DJ and still obsessively digs crates.

That is a fairly close approximation to Radio Paradise: https://radioparadise.com/home

Radio Paradise is very much a rock station at heart, so necessarily for everyone's liking. If you're into classic rock mixed with contemporary rock, mixed with a bit of everything else, it's worth a shot.

Re: The lie of music discovery algorithms

#44

Post by im3w1l »

Retric wrote: post #16
BillFranklin wrote: post #5

This is great to hear, though I'm curious why photos on your phone / pinterest would be relevant to a recommendation system? Surely the biggest signal would be what Spotify already uses: the features of various relevant factors (your previous listening sessions, your current session, what other similar sessions look like, etc.), that said, their recommendation system is surprisingly terrible given how much easier mus…

YouTube’s algorithm isn’t very good for users because it doesn’t really separate mildly interesting videos that you finish from awesome content you loved. YouTube of course doesn’t care because they don’t make more money when you see something awesome.

How would you distinguish one from the other given the data youtube has?

Re: The lie of music discovery algorithms

#45

Post by nutshell89 »

I really wish Spotify or Apple offered the ability for the listener to simply listen all of the songs released on their platform on a day or a week, good or bad, and directly pay the artists for the songs listeners enjoy. Spotify's "New Releases" for example, tracks only music that major labels promote, or that fit a predetermined genre, or are similar to the songs and artists that you already listen to.

There are smaller services yes, which allow for independent promotion and distribution (Last.fm, RateYourMusic) but these have fairly obvious flaws in how the listener can approach new music (RYM pushes ratings first and foremost, and both last.fm and rym push trending artists to their users).

Instead, because the value of music is zero (really, negative since the number of listens, streams, album purchases, etc can fail to recuperate the cost to make it ), the act of distributing music presents economic risk unless the release itself can be controlled by the investors through advertisement or paid promotion.

Re: The lie of music discovery algorithms

#46

Post by a-french-anon »

bsenftner wrote: post #10

Music discovery has never worked for me, for the simple reason it's the lyrics, not the music. I listen to anyone speaking truth, (the truth I believe, of course), and that gives me a wide disjoint range of music, but they are all singing about political social truths. Marvin Gaye, Public Enemy, Rage Against The Machine, Beyonce, The Stranglers, The Jam, Psychic TV... It's the lyrics, and now today, we finally have t…

> with the lyrics, with the intellectual content of the music and not just the dressing.

> Marvin Gaye, Public Enemy, Rage Against The Machine, Beyonce

Thanks for the laugh, man, I needed it.

Re: The lie of music discovery algorithms

#47

Post by tpurves »

The real big lie is the idea that the recommendation algos were ever actually for the user.

The premise that many folks miss here is the idea that Spotify is, at best, thinly interested in recommending music that is good for YOUR interests. Spotify is the music business, and specifically the pop music business, has long discovered that's it's much more economically expedient to force feed musical taste onto the public than it is to chase the whims of organic hit-making. Payola is as old as recorded music. Spotify recommends what Spotify wants it's users to listen to. They have all kinds of side deals and marketing deals with labels, they have cheaper costs/royalties on some tracks than others. Popular tracks cached in their CDNs are probably cheaper to recommend than long tail ones etc. They have strategic priorities like gaining on apple for podcasts, and therefore injecting allsorts of podcast recos in the UI wether you asked for that or not.

Re: The lie of music discovery algorithms

#48

Post by nihzm »

rickdeckard wrote: post #33

"They are not suggesting new, very interesting melodies. They are finding you the tweaked versions of the songs you already like and, even on your first listen you can predict the melody that’s to come." I really don't think that's the main method of Apple Music or Spotify to create a list of suggestions. From what I know, (beside of dark marketing-patterns) the suggestions are created by checking what other songs pe…

> This indicates that the persona that this platform created for you is quite homogenous and probably matches closely with many other personas on the platform

To add to this analysis, I think there may also be a feedback component to this problem that exacerbates the issue, since most users are passively using the suggestion algorithm.

In other words, if the suggestion algorithm tends to create a homogenized persona of the user's taste, say, because they don't bother to actively correct it, then this persona is embedded into a cluster of people with similar personas. And because the persona is now closer to said cluster, the suggestions will become even more homogenized. Moreover, since the cluster is mostly composed of passive users, the cluster itself will tend shrink (eg in variance) and to get more homogeneous.

I suspect that most algorithms do not do enough to prevent this global trapping effect, and so even if they have some method to sample "something new" for the user this becomes less and less efficient as more users rely on the algorithm for their suggestions.

Re: The lie of music discovery algorithms

#49

Post by stemlord »

I figure the problem is access. You either have the obscure music people want to discover in your db or you don't. The music available on spotify is a drop in the ocean so it doesn't really matter how searches work because a majority of the possible results simply aren't known by the platform
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