The best ”algorithm” for discovering new music was digging through profiles on last.fm back when the social functions of the site were still active. Sure, it was a lot of manual work, but the results were amazing. It wasn't completely blind, I found that people I had high similarity with, it was more likely I'll like what they like, even across different genres. Sometimes people were nice and took the effort to recommend based on my profile. I got introduced to varied music, different genres and even a bit from different countries.
The worst was Pandora, which did recommendations based on breakdown of musical instruments and elements in the song. It did what it aimed to do pretty well, only it was a bad idea. It gave you a lot of uninspiring music that sounded like a bland copy of something you actually liked.
Spotify's recommendations are not super awful, but definitely feel closer to Pandora's style. I wonder why is the result like that even though I'm sure they train their model based on listening history.
I used to pay for their radio service, it was a bit like Pandora. I found it when they added it to Xbox 360 as an app.
I really liked their original profile pages that had sort of a MySpace style customization & vibe. You could have your favorite musicians and tracks analyzed through their API by these 3rd party services that would create very cool graphics & charts to show off to friends and visitors what you were into.
But, then I guess they ran out of money and were really trying to get scooped up by Spotify. They turned off their music player, disabled all the profile customization, alternative services quit having built in scrobbling to it.
I remember I had to download an app that would constantly have my microphone open and it would ID the song I was listening to via some kind of Shazam service and send it to last.fm. I never considered what a security risk that was because I was more interested in keeping my last.fm music tracked.
The best way to discover music nowadays is RateYourMusic. I go to an album I like, read a couple reviews to find like-minded people and check out their profiles. They often have lists with their favorite albums.
The album chart queries are also incredible. The site has a very detailed system of genres and descriptors so you can find exactly what you want.
> The site has a very detailed system of genres and descriptors
My problem with this is that it makes certain assumptions about the consistency of applying genres and about the very concept of genre which (imo) is more of a social construct than an empirical concept. It falls in the same category as religion-sect, language-dialect.
what.cd was the world's greatest music discovery mechanism. You could always ask for recommendations in the forums or in the comment thread of the albums pages. The community always delivered. I miss that type of camaraderie. I also spent more on music as a member of that community than since it has been disbanded.
What.cd was the Library of Alexandria for recorded music, the depth of what was collated and properly labelled there was far beyond anything that has ever existed on any other service, paid for or not. Every permutation of every release, endless live recordings, often multiple of the same event, absolutely incredible.
OiNK before that, too. Once waffles and what disappeared then I was never 'able' to get on to one of the newer ones… the whole process is some real archaic thing. Used to have a great 'profile' on those others, but yeah.
My favorite manual discovery/social was Napster, for that moment that you could view other user’s entire shared music folder and use the chat function to talk to them about their tastes!
I was just talking about this in r/piracy but I remember there was a chat function on Kazaa where you could message people you were downloading music from and ask for recommendations. Simpler times...
> I found that people I had high similarity with, it was more likely I'll like what they like, even across different genres.
This has been until very recently the modus operandi of most recommendation engine algorithms. If an algorithm is essentially doing what you do, would you not like that?
In my experience Spotify's song/playlist recommendations are not great, but the album recommendations have a pretty high hit rate. I'm not sure why this would be.
Did they get a lot better recently? For years I rarely even looked at them because they were so banal and repetitive, but about six months ago they suddenly became something to stay on top of.
So, all I’m hearing is that, when we actually took the humans out of the loop and replaced them with algorithms, all the humanity disappeared?
”If take human out … why human there no more???”
It’s shocking this species is able to come up with such advanced technologies when the above is the existential question that plagues them in the macro.
I find it funny and sad that people get so excited about those Wrapped year-end things on Spotify when these companies are basically withholding all this data all year long and then pretend like it's a special treat when they doll out a peek at it once a year.
It feels to me like "dark mode" (which is a merely single color of customization for an app). We expect so little from our software and services that even these little, previously common features are supposed to be a treat.
Anyway, Last.fm was great -- I never used it that much for discovery, but rather to get insight into what I was listening to. Largely, it didn't say THAT much about my habits because I mostly just listened to my collection on random. My top bands were, for the most part, the bands I had the most of.
I'm on a music discord server (for metal), most people share their weekly, monthly, quarterly, and yearly charts made from their last.fm data. Here's what I posted yesterday for my weekly: https://i.imgur.com/6jYS8jG.png
>I find it funny and sad that people get so excited about those Wrapped year-end things on Spotify when these companies are basically withholding all this data all year long and then pretend like it's a special treat when they doll out a peek at it once a year.
Skill issue. you can export your listening history whenever you like.
If you use Spotify, you can download your full listening history here: https://www.spotify.com/us/account/privacy/. You get it in a pretty convenient JSON format and with a little bit of code it's pretty easy to create some visualizations.
There are also websites for visualizing this data. I'm quite fond of this one: https://explorify.link/. It allows you to do some custom queries.
I build a web app years ago with Spotify SDK to display top artists, songs, recents, also with a Discovery section that generates new music based on your history. You can create playlists from all sections. free @ https://echoesapp.io
Note that apps built from the SDK don't have access to the full history, only up to some cutoff. I tried a couple over the years and wrongly concluded Spotify deleted your history after some time.
The data download does contain everything, which was a very pleasant surprise. I didn't think I'd ever see the data from the couple years gap in my last.fm.
Last.fm is still used quite a bit, mainly as a listening history tracker rather than a radio or recommendation engine.
Spotify is still the only big streaming service with native platform-level scrobbling. For everything else it's a lot more DIY, usually with third party tools at the device level.
A big reason it’s still relevant is the ecosystem around it. The API hasn't really changed in 15 years, which makes it easy to build tools where a username alone is enough. That kind of lightweight social integration has mostly disappeared elsewhere.
Today, the social / community side is almost entirely just Discord. Nearly every music related server has a bot that displays Last.fm stats. My estimate is that abut 10% of Last.fm their users are also active in Discord music communities.
(Disclaimer: I run .fmbot, a Discord bot that integrates with Last.fm.)
These integrations are lacking compared to Spotify. For example in Tidal you have to set it for each device where you install the app, and it doesn't work with things like casting. It's easy to forget to set it up which can cause gaps in your history.
The Plex integration gets pretty close to native, but it only scrobbles after a track is done, it doesn't have 'Now Playing' support.
As for Deezer and Quobuz I'm not sure. Afaik Spotify still stands alone by being set-and-forget, working on any device and having full feature support.
Yeah, this seems to be the case for a lot of people. I frequently get support tickets asking how to connect Apple Music. There are some alternative players you can use, but it's not really an accessible solution suitable for mainstream use
Other recommendations in other siblings, but Neptunes on macOS and Finale on iOS are excellent. I only got into it a couple years ago, but aside from a few quirks, using those two has been super smooth and easy.
Last.fm isn't really expanding their API unfortunately. You can however see Last.fm stats in the main artist/album/track commands.
As for spammyness, I'm aware this is an issue. For non-bot channels I recommend using .togglecommand and enabling just a few specific commands, and setting a small embed mode so .fm commands don't take up too much space in chat.
Just one admin's opinion, but I think the bot spam thing is more a matter of server etiquette than anything. Sure, I'm all for #bot-spam channels, but nobody looks at those unless they're using it, so it's not very useful for things like sharing last.fm stats. I'd much rather people use it sensibly in a #music channel.
I love last.fm with all my being. I recently created a ListenBrainz (same org as MusicBrainz) account which is an open source alternative that you don’t have to host yourself. I’m scrobbling to both places now just in case.
Check out tapmusic.net too to make cool diagrams out of your scrobbled music.
I'm using selfhosted multi scrobbler [0] to scrobble to lfm, listenbrainz, and selfhosted koito [1].
Maybe not super useful, but fun ;) when at home, I scrobble to MS which distributes the data, when I have no VPN active on the go, I scrobble to last.fm only, which then gets used as source by MS as well, to redistribute it to the others.
I still use Last.fm! I've had it since 2008. It's really cool seeing how my music taste has changed, and seeing what I've come back to over and over again.
When I used to be much more active in online music communities I would post a 9x9 of my most listened to albums of the past week and discuss them.
Still scrobbling since 2008. A lot of smaller artists used to upload their music to last.fm, and I found a lot of gems there (specifically in the swedish bitpop scene).
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The worst was Pandora, which did recommendations based on breakdown of musical instruments and elements in the song. It did what it aimed to do pretty well, only it was a bad idea. It gave you a lot of uninspiring music that sounded like a bland copy of something you actually liked.
Spotify's recommendations are not super awful, but definitely feel closer to Pandora's style. I wonder why is the result like that even though I'm sure they train their model based on listening history.
I really liked their original profile pages that had sort of a MySpace style customization & vibe. You could have your favorite musicians and tracks analyzed through their API by these 3rd party services that would create very cool graphics & charts to show off to friends and visitors what you were into.
But, then I guess they ran out of money and were really trying to get scooped up by Spotify. They turned off their music player, disabled all the profile customization, alternative services quit having built in scrobbling to it.
I remember I had to download an app that would constantly have my microphone open and it would ID the song I was listening to via some kind of Shazam service and send it to last.fm. I never considered what a security risk that was because I was more interested in keeping my last.fm music tracked.
The album chart queries are also incredible. The site has a very detailed system of genres and descriptors so you can find exactly what you want.
simple, very little time investment required and avoids most modern fuckery
My problem with this is that it makes certain assumptions about the consistency of applying genres and about the very concept of genre which (imo) is more of a social construct than an empirical concept. It falls in the same category as religion-sect, language-dialect.
Dead Comment
You can even save their top songs as an auto-updating playlist. It's a great way to find new music that is not controlled by algorithms.
Here's my profile if anyone wants to have a look: https://volt.fm/soheilpro
This has been until very recently the modus operandi of most recommendation engine algorithms. If an algorithm is essentially doing what you do, would you not like that?
”If take human out … why human there no more???”
It’s shocking this species is able to come up with such advanced technologies when the above is the existential question that plagues them in the macro.
It feels to me like "dark mode" (which is a merely single color of customization for an app). We expect so little from our software and services that even these little, previously common features are supposed to be a treat.
Anyway, Last.fm was great -- I never used it that much for discovery, but rather to get insight into what I was listening to. Largely, it didn't say THAT much about my habits because I mostly just listened to my collection on random. My top bands were, for the most part, the bands I had the most of.
Eventually the stats became live updating and a bit of fun was lost.
Skill issue. you can export your listening history whenever you like.
Deleted Comment
If you use Spotify, you can download your full listening history here: https://www.spotify.com/us/account/privacy/. You get it in a pretty convenient JSON format and with a little bit of code it's pretty easy to create some visualizations.
There are also websites for visualizing this data. I'm quite fond of this one: https://explorify.link/. It allows you to do some custom queries.
Note that apps built from the SDK don't have access to the full history, only up to some cutoff. I tried a couple over the years and wrongly concluded Spotify deleted your history after some time.
The data download does contain everything, which was a very pleasant surprise. I didn't think I'd ever see the data from the couple years gap in my last.fm.
Spotify is still the only big streaming service with native platform-level scrobbling. For everything else it's a lot more DIY, usually with third party tools at the device level.
A big reason it’s still relevant is the ecosystem around it. The API hasn't really changed in 15 years, which makes it easy to build tools where a username alone is enough. That kind of lightweight social integration has mostly disappeared elsewhere.
Today, the social / community side is almost entirely just Discord. Nearly every music related server has a bot that displays Last.fm stats. My estimate is that abut 10% of Last.fm their users are also active in Discord music communities.
(Disclaimer: I run .fmbot, a Discord bot that integrates with Last.fm.)
That's not true. It's missing from Apple Music but present in Tidal, Deezer, and Quobuz. It also works well with Plex.
A large list from them: https://support.last.fm/t/more-ways-to-scrobble/192
The Plex integration gets pretty close to native, but it only scrobbles after a track is done, it doesn't have 'Now Playing' support.
As for Deezer and Quobuz I'm not sure. Afaik Spotify still stands alone by being set-and-forget, working on any device and having full feature support.
Also thanks for your work, while I dislike the spammyness of it, that's on the server owners (main server I'm on limits it to one bot channel)
As for spammyness, I'm aware this is an issue. For non-bot channels I recommend using .togglecommand and enabling just a few specific commands, and setting a small embed mode so .fm commands don't take up too much space in chat.
Check out tapmusic.net too to make cool diagrams out of your scrobbled music.
Maybe not super useful, but fun ;) when at home, I scrobble to MS which distributes the data, when I have no VPN active on the go, I scrobble to last.fm only, which then gets used as source by MS as well, to redistribute it to the others.
[0] https://github.com/FoxxMD/multi-scrobbler
[1] https://github.com/gabehf/Koito/
Then again, if all it does is collages, then ListenBrainz has a tool for that of its own.
https://en.wikipedia.org/wiki/Oink%27s_Pink_Palace
Dead Comment
When I used to be much more active in online music communities I would post a 9x9 of my most listened to albums of the past week and discuss them.