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The lie of music discovery algorithms

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Re: The lie of music discovery algorithms

#61

Post by Retric »

HPsquared wrote: post #31
Retric wrote: post #16

Earlier quoted context omitted.

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.

It works pretty well for me. Do you use the like and dislike buttons, subscribe to channels you like, etc?

> subscribe to channels you like

That makes things worse IMO. My favorite videos tend to be one-offs not channels producing regular content. Unsubscribing from everything definitely improved my feed.

Re: The lie of music discovery algorithms

#62

Post by quxbar »

> 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

This seems like the complaint of somebody who hasn't been using spotify very long. After a decade plus, I feel like my algorithm is a rich compost pile of all of my previous phases of music. Spotify is excellent at letting me broaden my horizons or jump down a rabbit hole from a random starting point, like a song I hear in a public space or commercial or something sent by a friend. Maybe the OP should keep their ears open to more sources of randomness from the outside world?

Re: The lie of music discovery algorithms

#63

Post by gtpedrosa »

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…

Instead of relying on things like "Playlist made for you" I still like leveraging the algorithm to discover "new vectors" by actively going to a song that some aspect caught my attention and going to its radio (only tried on Spotify). Sometimes I'm surprised with new soundscapes.

Re: The lie of music discovery algorithms

#64

Post by InitialLastName »

quxbar wrote: post #62

> 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 This seems like the complaint of somebody who hasn't been using spotify very long. After a decade plus, I feel like my algorithm is a rich compost pile of all of my previous phases of music. Spotify is excellent at le…

I feel the opposite: my Spotify recs (after at least 8 years with an account) tend to get stuck on whatever I've been listening to recently. I've had to consistently go afield to find any new (to me) music. Even their "new releases for you" falls short of recommending me releases from artists I follow. How much less capable could it be?

Re: The lie of music discovery algorithms

#65

Post by 2big2fail_47 »

mushufasa wrote: post #19

No music discovery algorithm has satisfied me. All data-driven approaches make predictions based on historical data. Personally I enjoy being exposed to entirely new genres and sounds I've never heard before, instead of variations on genres I've listened to a lot. My solution: listening to NTS, an eclectic online radio station, where diverse artists create playlists.

Love NTS. Human-curated radio is still the best way to find new music :)

Re: The lie of music discovery algorithms

#66

Post by Capricorn2481 »

On Reddit, there was a few threads where people were reporting that, no matter what song radio they listened to, they were getting Sabrina carpenter. Didn't matter if it was Rap, Sad Indie, Vaporwave; She would eventually come on.

It's noted that her current tour is sponsored by Spotify.

Re: The lie of music discovery algorithms

#67

Post by AdmiralAsshat »

corytheboyd wrote: post #58

Personally all I want out of a subscription based music service is excellent quality, constantly updated/created, thematically consistent, human curated playlists. I don’t really care if it’s super popular or fringe stuff, but I do want it to be as “good” as the other stuff on the playlist, and I want a human who also cares about the music to be making that decision. Sometimes the playlists in Apple Music scratch thi…

I've got a Tidal subscription, and I've played with creating a few of my own playlists for the explicit purpose of sharing with others (as opposed to personal use). They're nothing special, but I at least try to put in some research while constructing them to bound them at a narrow time-frame/genre for accurate historical purposes.

I have no idea if anyone is listening to them, though, because there doesn't seem to be any feedback system for the community playlists. That would be a useful addition, IMO. If TIDAL doesn't want to pay dedicated staff to curate playlists, they could at least make some way for the member-created playlists to get featured or gain reputation.

Re: The lie of music discovery algorithms

#68

Post by bocytron »

corytheboyd wrote: post #58

Personally all I want out of a subscription based music service is excellent quality, constantly updated/created, thematically consistent, human curated playlists. I don’t really care if it’s super popular or fringe stuff, but I do want it to be as “good” as the other stuff on the playlist, and I want a human who also cares about the music to be making that decision. Sometimes the playlists in Apple Music scratch thi…

Deezer has human curated playlists updated frequently, which has been my main way of discovering new artists these days. For example, the prog metal playlist as been updated 5 days ago. [0] There are lots of those playlists..

[0] https://www.deezer.com/fr/playlist/1588605745

Re: The lie of music discovery algorithms

#70

Post by somethingreen »

diob wrote: post #57
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…

I'm not sure how the Spotify recommendation algorithm works at all, but for some reason I imagined them doing fancier things than looking at my liked songs and finding similar ones. I would've thought they'd build a profile of you, and then find similar user profiles and show you songs those folks liked that you hadn't found yet. That's gotta be how they do it, right? I'm probably wrong.

I feel those are how Pandora and Last.fm (used to?) work respectively. Nowadays everything seems to just put a bunch of tags on a track and suggest you things with the same tags to the tracks you liked. Doesn't even need to match the same combination of tags, just some number of them. The problem is, you probably care about the small, specific tags, and the system cares about wide "popular" tags. If you like a couple niche genre covers of songs that happen to be featured in TV openings/OSTs, you are not getting more songs in that genre - you are getting a bunch of covers and OSTs.
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