* "good fit"/"bad fit" button — I like a wide variety of music, but it needs to be appropriate to context. If I start a radio from a song, I'd like to teach it to tailor the suggested songs better but that doesn't mean I dislike the songs it _is_ suggesting.
* Ability to give the social context — a band playing at a music festival will lean more towards hits in their back catalogue. At their own gig they may play some obscure stuff that die hard fans will really like. Similarly, what I'm listening to will be different if I'm having a party, friends over for dinner or on my own. On a family account, you should also be able to say who is listening & it should tailor to music that you might all enjoy.
* I get that they don't want to block artists/songs completely but they _should_ allow limiting how many times they suggest it per day. If I've listened to Everywhere by Fleetwood Mac on one playlist I probably don't want to hear it again an hour later on another playlist
I haven't used it in a while, but this was a big advantage of Pandora for me. With pandora, you start a 'station' with a few seed songs and as you like/dislike songs, it keeps refining the station.
The downside to Pandora is that you can't choose your music. You can seed a station with a specific song, but that song might not be the first one played.
What I really liked with Pandora was that it was really good at producing endless playlists for me to listen to at work or car rides. I was a paid subscriber when I worked night shifts and drove a lot more. Spotify stations are really hit or miss. Sometimes the Spotify stations dive into foreign music and I can't find a way to specify which language of music I want to hear.
I have good and bad experiences with Pandora. The biggest issue was telling it I didn't like a song and having it recommend another mix of the same song. Dislike that one and get yet another mix of the same song
I worked in a shop where 8 employees were constantly voting amongst ourselves to up-vote/down-vote each song as it appeared on a given Pandora station/playlist that was broadcast throughout the shop. This made for a great sense of consensus and discussion amongst a group of music nerds.
However, one issue with Pandora was that no-matter the genre it would inevitably throw in a song by Morrissey, which would be met by a round of groans and calls by everyone in the shop to aggressively down-vote the song. The joke became that all roads eventually lead to Morrissey.
I have had a great time exploring the entrances to various rabbit roles with pandora, but once I try to actually descend deeper and really narrow the focus I experience the same behavior. It's like it just doesn't have a big enough catalog and is pulling from too small a pool.
Like some others have said, I've found Deezer's flow (shuffle algorithm) to give the best results. I've been using it for a few years now, so I have no idea how fast it could learn for a newcomer.
They just added a "moods" choice to flow a few days ago: focus, sport, party... I think there are 6 of them. But they added it only to the mobile app and not the webapp which is the one I use the most, so I can't really say how good they are.
Deezer flow is my go to for this, and they've recently added moods, which really helps.
I find I often start flow, get a few songs in and jump onto an album based on the currently playing song. Really great for discovery of music I've not heard (before or for a while).
Spotify seems to always end up merging back to some generic tracks that I've heard so many times before.
That said, I've been training Deezer (they have both like and dislike, as well as never recommend song / artist) for over 10 years, so they better get it right!
I spent the latter half of 2019 trying to build this as a startup. Ultimately I pivoted (now I do newsletter recommendations instead), but if I hadn't made some mistakes I think it could've gotten more traction. Mostly I should've simplified the idea to make it easier to build. If anyone's interested in working on this, here's what I would do:
(But first some background: The way I saw it, you can split music recommendation into two tasks: (1) picking a song you already know that should be played right now, and (2) picking a new song you've never heard of before. (Music recommendation is unique in this way since in most other domains there isn't much value in re-recommending items). I think #1 is more important, and if you nail that, you can do a so-so job of #2 and still have a good system.)
Make a website that imports your Last.fm history. Organize the history into sessions (say, groups of listen events with a >= 30 minute gap in between). Feed those sessions into a collaborative filtering library like Surprise[1], as a CSV of `<session ID>, <song ID>, 1` (1 being a rating--in this case we only have positive ratings). Then make some UI that lets people create and export playlists. e.g. I pick a couple seed songs from my listening history, then the app uses Surprise to suggest more songs. Present a list of 10 songs at a time. Click a song to add it, and have a "skip all" button that gets a new list of songs. Save these interactions as ratings--e.g. if I skip a song, that's a -1 rating for this playlist. For some percentage of the suggestions (20% by default? Make it configurable), use Last.fm's or Spotify's API to pick a new song not in your history, based on the songs in the current playlist. Also sometimes include songs that were added to the playlist previously--if you skip them, they get removed from the playlist. Then you can spend a couple minutes every week refreshing your playlists. Export the playlists to Spotify/Apple Music/whatever.
As you get more users, you can do "regular" collaborative filtering (i.e. with different users) to recommend new songs instead of relying on external APIs. There are probably lots of other things you could do too--e.g. scrape wikipedia to figure out what artists have done collaborations or something. In general I think the right approach is to build a model for artist similarity rather than individual song similarity. At recommendation time, you pick an artist and then suggest their top songs (and sometimes pick an artist already in the user's history, and suggest songs they haven't heard yet--that's even easier).
This is the simplest thing I can think of that would solve my "I love music but I listen to the same old songs everyday because I'm busy and don't want to futz around with curating my music library" problem. You wouldn't have to waste time building a crappy custom music app, and users won't have to use said crappy custom music app (speaking from personal experience...). You wouldn't have to deal with music rights or integrating with Spotify/Apple Music since you're not actually playing any music.
If you want to go further with it, you could get traction first and then launch your own streaming service or something. (Reminds me a bit of Readwise starting with just highlights and then launching their own reader recently). I think it'd be neat to make an indie streaming service--kind of like Bandcamp but with an algorithm to help you find the good stuff. Let users upload and listen to their own MP3s so it can still work with popular music. Of course it'd be nicer for users in the short term if you just made deals with the big record labels, however this would help you not end up in Spotify's position of pivoting to podcasts so you can get out of paying record labels. And then maybe in a few decades all the good music won't be on the big labels anyway :).
Anyway if anyone is remotely interested in building something like this, I'll be your first user. I really need it. Otherwise I'll probably build it myself at some point in the next year or two as a side project.
I have found song, artist and playlist radio to be extremely effective at discovering new music. For example, Monday rolls around and I hit my discover weekly, say I like a song, I hit the song radio and go down a discovery rabbit hole, try it.
Good fit/bad fit would be genius. My musical tastes can be all over the map. From 80s pop to jazz and swing. Sprinkle in some Icelandic metal and rap and hip/hop. Don't leave out the occasional polka or Taylor Swift. My moods can change day to day and a more accurate playlist would be a Godsend.
1, Give me a way to mark a period of time or specific songs in my history as not to be used to inform my recommendation model signals. I might want to put on some special themed dinner music or listen to a song a few times for a certain reason but otherwise not want future recommendations informed by this.
2. Give me a a genre or other filter. Sometimes recommendations will be great but are a mix of soothing guitar and hard trance. I don't necessarily want both at once.
3. Give me a way to use one song in my weekly discovery and say "remove all songs in the current list that are like this and don't give me any more ever again." Like, I put on classical once, and for months now most of my discover weekly is stuff I have zero interest in. I can go one by one but really I need a "dislike type/genre" button.
Upon reading the parent comment, I don't think this is what they were suggesting. They were making an analogy between what a band chooses to play live at a show based on context of the show, and what a streaming service could do to suggest songs based on context of the listening environment.
Yes, if you want to curate an entire playlist. Not everyone does. And if anyone has the enough data to generate these kinds of disparate playlists on their own with minimal user input/direction, it would be Spotify.
I don't really follow. If we're talking about something so specific as "what songs would a band play on their own set list" that should be manually curated, and in a very short amount of time.
If it's just general vibes... spotify already does this for you. They have an entire section called "Made for you" which seems to cluster your tastes and generate playlists of them.
Perhaps you just want to generate a cluster off of your own chosen centroid of song profiles. That could be cool I guess. I vastly prefer to just play albums.
They’re saying they want even more specific ”made for you” features - not just tailored for a person, but tailored for a person and a certain context (like they mentioned as examples - when they’re on their own, when they’re having dinner with friends, when they’re throwing a party etc). Presumably you would tell the app what your current setting is.
I guess I don't really buy that this isn't served well by genre or artist based playlists. How much more nuanced are you going to get than saying "I want to play some alt pop" for this party.
A dislike button would be handy. There is that feature on some of the generated playlists, but I don't think they do anything. My two biggest issues with Spotify right now are:
1. Release Radar filled with re-releases and remixes, often from artists who have long since passed away. I want new music as in released for the first time.
2. Name collisions. I'm surprised this is an issue, but I will often get songs from different artists with the same name. And then I'm unsure if selecting "I don't like this song" or "I don't like this artist" will affect the actually intended artist.
I've also reached a tipping point where I no longer find new music through algorithmic recommendations. To be fair it's taken about 5 years to reach this point. Now the good music I find comes from searching for curated playlists. It's come full circle as before streaming I got my music recommendations from blogs and friends.
Agree on the above (though are duplicates really that much of a practical issue? I did discover some Russian rap through that). I'd like to add:
3. Discover Weekly stuck recycling through the same songs over and over again (it's also years since the algorithm found anything new for me, apart from name collisions)
4. Geo-language-locking. My CC will apparently only be accepted with its registered address in Spain. I barely speak a word of Spanish and don't have interest in the music popular in Spain. Yet it's what they keep pushing me, especially podcasts (including any episode in generated lists). Long-standing issues on all their community forums for this, eg https://community.spotify.com/t5/Live-Ideas/Browse-Allow-to-...
I recall a 100+ page forum thread on 4 but can't seem to find it now.
Curious: how repetitive is your listening history?
I also notice that my Discover Weekly and Daily 1-5 playlists are recycling much of the same material. But I also frequently listen to my Liked Songs (< 40 songs) on shuffle, so I assume Spotify's algorithm is looking at that data and saying "you do actually just want to listen to these songs over and over again"
Otherwise, a fun experiment I tried last year: deleted all liked songs, all playlists, etc. to refresh my recommendations. I didn't pay close attention to how new suggestions compared to old, but it was one sort of trick to find new stuff rather than heading back to existing playlists. My Liked songs definitely aren't those from last year.
Also, this may seem counterintuitive but I regularly listen to playlists that seem like they are out of my interest pool (e.g. will deliberately check out a country playlist) as another way to move away from my own recommendations.
I listen to a workout playlist on shuffle frequently while training, while slowly adding new music to it throughout the year.
Like others have mentioned, Spotify has completely stopped recommending new music for years now. Even if I start a song radio from a song I've never listened to before, Spotify immediately just starts playing songs from my current year's workout playlist. That is not the behavior I want. Yes, I listen to that playlist a lot, but when I'm not listening to that playlist, I'm trying to find new music. It seems really obvious that that would be the expected behavior, to me at least.
This has a lot to do with your present listening habits, unfortunately. 7 years in, I still get new stuff in discover weekly, though there are also a good deal of repeats which are frankly "discoveries" as far as Spotify is concerned, but nothing new from my perspective. Basically, Spotify is also recommending I listen to stuff I used to listen to a lot before I started using it (and could therefore afford to listen to more than just whatever was loaded on my phone at the time)...
It was a manual process for me personally, finding them through message boards and forums (I know that's not much help). I'd also use https://www.music-map.com. /r/listentothis on reddit is also a good source of tracks.
What I mainly do now is look for Spotify playlists by record labels that represent artists I like, or look for playlists made by artists I listen to.
Shout out to holyfuckingshit40000 on blogspot, it's long gone now. But that was my favourite music blog, to the point I wanted to meet the person who ran it and buy them a drink or something, because almost everything they recommended I loved. Just now I've found that someone compiled a list of the recommendations, check it out: https://joseph.pallamidessi.fr/2020/05/03/holyfuckingshit400... (it's missing some from memory, but it's a diverse collection of some good music).
A few months ago, I started listening to new-music programs on BBC Music Introducing [1], particularly the London program [2]. As you might guess from how I spell “programs,” I’m not British and have never lived in the U.K. But I’m an older guy who responds most viscerally to the same old songs I liked as a teenager. Listening to music created by young people today helps to get me out of that rut.
Sasha Frere-Jones used to be the music critic at the New Yorker and writes a fantastic (although somewhat irregular) substack blog > https://substack.sashafrerejones.com/
I frequent the bandcamp daily blog, and I follow a few people on bandcamp who tend to actively buy music I’m interested in (I just go through the users who have bought an album I like, then I look at their other purchases). On top of that bandcamp sends me a weekly “you may be interested in” email that often has at least one thing I’m actually interested in.
I read some blogs. But overall I discover a lot on bandcamp - more than I can process.
Unfortunately the only thing they seem to do is exclude that song from that playlist. I've had things I disliked on one radio station come up on a different station 30 minutes later.
I just recently switch to Spotify from YouTube Music (as a former diehard Google Play fan) maybe 6 weeks ago. Everyone raved about how great the recommendation system was but I'm certainly not seeing it yet after spending several weeks diligently liking/disliking songs, entering in favorite artists, etc.
2. "Name collision" unfortunately that's not Spotify's fault but the artist who set the wrong Artists ID. So instead of creating a new one for themself, they just use an already existing one with the same name. What I did in the last i just email the record label ( if they have one ) and ask them. In my case i listen to metal, but every know and then a mediocre rap song shows up in my RR. Usually because the artist is clueless and they just "put they new song" on Spotify.
Entity resolution is a thing though, and the Discover Weekly algorithm actually tries to combine artists (possibly due to collaborations), which is what goes wrong.
For example, I follow Cornelius, the Japanese guitarist. I liked several of his song. So the data indicates I’m a fan. I’ve been recommended a new song by a different Cornelius. This other guy is an African gospel singer. I don’t follow him. Never even played a song.
That shouldn’t happen. The system knows they’re different Corneliuses, because the catalogs aren’t mixed, but yet string match took over.
I wonder if, instead of a string match, enough people have searched “Cornelius” and (accidentally, out of curiosity, etc.) played the gospel singer’s songs that it’s algorithmically linked the gospel singer to the other artists these people listen to, which are then linked back to the Japanese guitarist.
No, you have to sign up with a company Spotify has a deal with. Spotify seems to no longer have a deal with the sort of "artist services" companies that don't check if the uploaded music is a Beyonce album.
Spotify, or rather the old Echo Nest folks I suspect, actually do a lot to combat spam compared to the other streaming services.
I tried out the French service Deezer for a while, they had a huge compilation spam problem. I found one spammer in particular, who around four times per months would upload 300+ albums, all with the same title and cover art, only the artist name would be different. Thus you would get the album "Angry Man" by Frank Sinatra, "Angry Man" by Charles Aznavour, "Angry Man" by Johnny Rivers, etc. for another 300 artists. Thing is, they would contain music from the actual artist. The spammer probably speculated that if you wanted to add, say, Doc Watson's "Sitting on top of the world" to a playlist, searching would lead you to one of his "compilations" instead of the original. Or maybe it's part of a scam with hacked accounts "listening" to these teams. Either way, it must have been profitable, because with some searching I found out he'd been at it for almost a decade. He uses one of the "artists services" companies that lets him pick a new label name every time, but his laziness in generating images reveals it's the same guy (and I'm pretty sure I know his name, too).
He's not on Spotify, they kicked him off ages ago. But he's on literally every other streaming service that I know.
Spotify at least seems to have a few humans employed to take tips about mislabeled releases and fix them. (For instance, they removed the albums of the Salvadorean rapper Spiro from the page of the British folk band Spiro when I mailed them about it.) Most streaming services have nothing of the sort. Music metadata sucks, but Spotify is actually slightly less godawful than the norm.
My problem with "Release Radar" are all the singles (and, as you say, remix stuff; sometimes it's an EP with one original track and multiple remixes). If a musician I follow releases a single, I'm not really interested until it's actually released on an album. So the only way to consume "Release Radar" is to click into every release to look at what's inside.
As for the "dislike an artist and I'll dislike all artists with the same name", you could theoretically compare the two by artist-ids, which you can see when sharing the artist through the Spotify client or using a browser to show the profile.
Spotify usually doesn't just give the same ID to several artists with the same name, but of course it's not impossible.
I'm genuinely confused by people who complain about Spotify's recommendation algorithm. I have eclectic, often obscure tastes, and I've found it to be an incredible way to discover new music.
I think you do have to prime the engine a bit. I "like" a lot of albums and songs. Every time I hear something new that I like I press the little heart button. Same when I discover music outside of Spotify (I listen to WFMU a lot). I make a lot of playlists. And I use the radio feature all the time. Click on the ellipses next to any song, artist, or album and you can "Go to radio" and Spotify will spin off a playlist of related music. I'm continually discovering new things that way.
My Discover Weekly and Release Radar playlists are always full of great stuff.
Spotify's recommendation algorithm comes with a healthy pinch of Payola. "Hey you've been listening exclusively to chiptunes and power metal from the 80s. Here's a new single from $local_mumble_rapper you might love!"
And you can't dislike the recommendation, so next week the algorithm is going to go "Oohh last week he played some mumble rap, let's give him a little bit more of it!"
I've been stuck in the same local optimum for years, getting the same songs and artists in the same genres (that I do and did like, but it's gotten old now)
I'm genuinely confused by people who complain about Spotify's recommendation algorithm. I have eclectic, often obscure tastes, and I've found it to be an incredible way to discover new music.
I too have "eclectic, obscure" tastes and I couldn't get anything from the recommendation algorithm and canceled after a month. I don't remember the thing recommending anything that seemed more obscure than what I searched for. And I made playlists.
But seriously, some people's tastes are served by Spotify and some find it frustrating. It would be nice if those who don't get immediate satisfaction had a more sophisticated approach available. My hunch is the company would prefer less customers and more control.
To be fair, the recommendations are based on what you listened to lately in addition to what you've listened to in the past. A month probably wasn't long enough - it isn't really an immediate satisfaction thing when you have off-center tastes in music. If 70% of folks like popular music, that's the easiest thing to recommend.
They might want a bit more control, I don't know, but I very highly doubt fewer customers is the goal. If they wanted fewer, they could just pull the free model completely. I'd guess piracy would increase and they'd get blamed, but I don't know.
To be fair, the recommendations are based on what you listened to lately in addition to what you've listened to in the past
So each day when my mood changes, I'm suppose start searching for a bunch of tunes and after an hour, I get what I want?
If 70% of folks like popular music, that's the easiest thing to recommend.
"Brilliant AI" ... turns into just top40 radio and victory is proclaimed.
They might want a bit more control, I don't know, but I very highly doubt fewer customers is the goal
This is what I said with a slightly different spin - they're willing to trade control for customers. Whenever companies engage in annoying or abusive policies that drive away customers, it's not that they don't want customers in the abstract, it's that they prefer control and profit margins over customers.
Yes, same, I enjoyed the weekly recommendations for about a year, each week being recommended some songs which remain favorites. But the algorithmic recommendations then got heavily skewed towards Finnish rap music. Which made the recommendations garbage. The convergence towards Finnish rap is not uncommon on Spotify.
I've never had the problem with Finnish rap, but at one point the discover weekly was full of death metal. Also, for some reason they pushed really hard Ricky's Hand by Fad Gadget (awful, but at the time they had a well hidden ban button), Swamp Thing by Chameleons (kind of OK, but don't they have other songs?) and Love Will Save You by Swans (kind of OK, but do have long discography so why always that one song?)
I did find it to be extremely poor but once I started liking individual songs, not whole albums it does better. Still, I'm not sure it uses other listening habits to feed the engine such as:
- Early skipping a song from a generated play list (-1).
- Repeat playing the same song from a generated play list (+1)
The algorithm often is very strange.
My mixtapes most often contain single tracks of audiobooks I listened to. Looks like Spotify treats audiobook tracks like any other song which is obviously very silly. Who doesn‘t want to listen to random audiobook snippets.
It’s really good for me. But I had a large catalog of mp3 accumulated over the years and then manually followed a ton of those artists and liked their tracks.
Good recommendations obviously require good data. You sort of get what you put in to an extent.
The radio feature is awesome to discover new music. You can make a short playlist of a few songs you like, and start a radio from that. You can later tweak the playlist to change what you get in the radio while it’s playing.
I also find it strange. I find the algorithm incredibly good. I did link it with iTunes back in the day, so it started off knowing what I like, and I always Like tracks when I like them. Now I often find myself pressing like on most tracks on Discover Weekly because it's so good at recommending things I'll enjoy, and quite a lot in Daily Mix and Artist Radio too.
I'm apparently in the minority, but I long for a return of the 5-star ranking. I really miss that about itunes, being able to rank each song, and set up smart playlists based on genre and how much variety (how deep in the star rankings) I wanted.
I'd have to think an intelligent recommendation engine could do a ton more with star rankings than a simple up/down too. 5=love, 4=like, 3=ok, 2=dislike, 1=hate. It could even be optional; they could just treat like and dislike as 4 and 2 or something, and let people who want more precision use them.
It needs more than that. I often hesitate to rank because my preference often varies by time and mood and setting. I might not dislike a song, but don't want it played when I want something mellow to fall asleep to, or when I'm happy or when I'm sad. Having a given song show up in one context might irritate me because it breaks the mood while I might love it another time.
A good recommendation system for music needs to take into account proximity in play order to other songs you've ranked when you rank it, and their tempo and genre, time of day, etc.
The more information the better, thing is platforms want to sell their content first and foremost. This removal of user input was pushed by the business so they could push content regardless of personal interest.
Ever wonder why Netflix keeps on pushing bad content ?
One reason to keep on pushing bad content despite knowing the user will not watch them is to hide the fact how small their catalogue is and shift the blame onto user's particular taste.
I don't have any written or direct evidence, however I worked for a public service broadcaster, who regularly dealt with Apple and Netflix, and the feedback from both was that star-rankings were driving a lot of royalty payments and user choice (people would ignore poorly ranked content). The impact of this was that low performing content providers made less money. By removing the collective scoring, the company would implement their own recommendations algorithms, which gave them the ability to both deliver 'better' recommendations based on what the user consumed and spread the royalty payments more broadly. If what you wanted was to see what everyone else was watching/listening to though, that's not in the interest of their business. Anecdotal and third hand but I believe the people that relayed this to me.
That makes sense, thanks for elaborating! I could imagine a different solution where instead you just don't report the overall star-average, to make it a harder metric to game, but still get to have a stronger feedback signal for your recommendations.
> "Netflix Ditches 5 Star Rating System, Is Amy Schumer to Blame?"
> "This past week, Netflix officially debuted their new Amy Schumer stand-up comedy hour The Leather Special. And it was instantaneously met with negative reviews. Some claim that Schumer's biggest critics got on Netflix and purposely drove down the rating of the special, some without even watching it. Schumer herself blames the 'Alt-Right' for sabotaging her latest effort. Now, it is being announced that Netflix is ditching its five-star rating system for something much more streamlined, a rating system that owes itself to the legacy of the late Gene Siskel and Roger Ebert. Did Amy Schumer have anything to do with this new rating system? Probably not. But once in place, it will certainly help her Leather Special find a more appropriate audience."
I'm pretty sure stars were discontinued because the best proxy for "what you will spend time watching, is what you spent time watching" and not your curated ratings. As in: the datapoint they funneled into their models was "time spent on video X" and not, "rating on video X".
Business of course wants to keep churn low, and they think time spent on the site is the best way to do that.
That (and "people mostly don't use ratings beside 1 and 5") is at least the reasoning I've read every time I've seen this topic mentioned in blogs/talks.
I do also feel Netflix is pushing it's in-house content way more these last few years, to the detriment of their recommendations though.
There are two issues with 5 star ranking. One the more thought required to give feedback the less likely users give feedback. More interactions is very helpful for ml so minimizing the decisions needed by a user helps a lot. Great ui/ux for engagement aims for signals to require as little action from the user as possible. As a side effect short content is very nice as finish/playtime become strong signals that require a user to do almost nothing.
The second issue is a lot of people use it like 1/5 system. While yes some users use more of the intermediates and you can adjust on per user basis for that feature it’s just not as useful as you’d expect.
Of course any decision like this I recommend a company ab test and I’m just summarizing past experience in this area.
I had a similar discussion at a prior job on having creators add content tags to there submission. The main avoidance was while good tags would be nice for recommendation, if tags are required less content would be submitted and that hurts the platform.
> One the more thought required to give feedback the less likely users give feedback.
That is great! This means the people giving feedback would tend to be power users that are able to giver higher quality feedback.
> As a side effect short content is very nice as finish/playtime become strong signals that require a user to do almost nothing.
Perfect! It is clear by now that users vastly prefer short content that gets to the point quickly.
So basically 5 stars ranking would vastly increase the quality of the content but that is bad, how?
The only issue I see is (political) vote brigading. Maybe set additional hurdles like minimum account age and the like for voting. Strong content moderation could help. I guess there is no silver bullet for that issue.
Your first point isn’t true because most of the 5 star usage boils down to 1/5 stars and not 2-4. There are some users that use whole range and the info does have value. The main problem though is while that system may be better for certain users, it will be worse for the entire user base as you want a system that works well for both casual and power users. Really you want a system that works better for casual users as most users on typical system like YouTube/spotify/tiktok/etc would be casual users. And while having model distinguish between user types is possible, ui wise you aren’t going to want to have both thumps up/down as an option and 5 stars. A toggle is possible but even for users that would use full ratings, a toggle is fairly unlikely to be used.
Even for power users it may not be net benefit for them. Recommendations are not based solely on that user’s ratings but all ratings. If power users give better signal but total quantity of signals decreases then it’s likely that recommendation quality drops for both casual/power users. Making up guess numbers a 5 star system is likely to get you 3x less data points and many of those data points are of similar quality anyway (users that only rate 1/5 stars). Worse signal that has higher volume often leads to better model.
My argument was based on the premise that votes from power users are more valuable as they better at judging the quality of the content. While the quality is partly subjective, it is not entirely so. Meaning power users, having more experience, know better what casual users should watch and would like then the casual users themselves. It is in the interest of the casual users for them to not be able to vote/their vote to count less.
I later suggested ways to make the hurdles for voting higher, which would fix the problems you mentioned. Required account age, maybe even how much content you need to have watched. Honestly, we could just filter out the people that only do 1/5 star votes. (With niche content of course there would be the issue of having no/just a few votes but voting would not be the only metric anyway.
I am very heretical towards common held UX believes and think trying to design for the lowest common denominator just results in all around awful experiences for everyone. We should rather strive to empower users.
> My argument was based on the premise that votes from power users are more valuable as they better at judging the quality of the content.
That is quite unlikely. What you call power user is someone distinguished by willingness to rank. It does not make that person better representation of all users or be more knowledgeable off quality or more experienced. Just more judgy.
It means you will be recommended based on tastes of special minority and likely alienate the rest of users in the process.
> My argument was based on the premise that votes from power users are more valuable as they better at judging the quality of the content.
As someone responsible for designing and incorporating end-user activity/feedback into ML, I have to tell you this is exceedingly unlikely.
The number of power users, especially on a large consumer app like Spotify, is dwarfed by the broad userbase (I estimate ~1% of Spotify users at most qualify as "power users").
Would I rather have power user-only feedback, or 100x the feedback? Definitely definitely 100x the feedback from all users.
I don’t think counting there vote less is useful. Low quality signal that is plentiful is very often better than sparse higher quality signal. My past experience is working on recommendation systems at tiktok/snap. Having a lot of weak signal from casual users is extremely helpful for power users. Recommendations are often based on large amount of basic engagement data. I think a large aspect to TikTok’s system being considered strong at recommendation is because Ux is designed for very frequent simple signals.
I can also say working at companies like that generally any system changes require an ab test and long running back test. I’ve generally seen companies move from 5 star to simpler like/dislike system and those changes would have been ab tested and found that user experience is overall better. I don’t know for specific systems whether overall better was across all users or some users.
I think these issues are more significant for public rankings. When I'm ranking songs, it's to curate my own listening. So if I only want to use 1 and 5 stars, fine—no worse off than a thumbs up/down system. But for those of us who do want to be more precise, it just gives more flexibility.
The systems I worked on were mainly for user curated recommendations and not public rankings. Your rating is only small part of your recommendation. A large amount of your recommendation is finding other users with similar ratings on similar content to you. If 1/5 star system leads to less ratings from other users, then system's ability to find similar users/similar ratings become worse and can negatively impact your recommendations.
I can't rate using 5 stars, it's either like, dislike or don't care, so 1 star 5 stars or no rating. With Tidal that's either listen to <30 seconds, skip or maybe listen through the full song, maybe fave or go back and replay. So they don't even need a dislike button. They just need to look at user actions if the algorithms are really optimized for tailoring content to the user's preferences, rather than pushing sponsored content in order to make money really fast. I don't even look at their recomendations (they're BS), but I do play artist radio if I happen to like something. That's how I found about Toshiko Akiyoshi a few days ago while listening to some artist's or track's radio.
Itunes (well I guess it’s Apple Music now) does still support 5-star rankings, it’s just hidden behind a context menu. I still have a Smart Playlist (can you even make those anymore?) of my 4-star and 5-star songs that serves as my daily shuffle rotation.
I have seen this article before. The author are so close to understanding why Spotify does NOT need a dislike button
>To dislike a song is easy – to like one, you have to actually invest time in it.
Likewise, to detect if a user dislikes a song is easy since the user will not invest time listening to it: the skip button is the dislike button.
In contrast, detecting if a user likes a song is more difficult: there needs to be a way to distinguish between a user enjoying a song and the user not paying attention (in that case the user will provide no input whether they like the song or not.)
I suspect that this same effect is close to the reason so many services removed the dislike button: humans are emotional and were, in some cases, disliking songs which they were not in the mood for, but would like at another time.
As a result, the signal coming from the dislike button was not very useful, and just added unnecessary complexity. Instead, the algorithm can present the user a fixed song in different settings to see if they continue to skip it. A nice result is that the user doesn’t have the negative reaction “hey I disliked this song why are you presenting it to me again”
I frequently will find one of their auto-mixes I like, and listen to it for a while throughout the day skipping songs I don't like or I'm not in the mood for. Then when I go back the next day, even if I didn't restart the mix, it has updated, and what plays isn't the stuff I liked and repeated. It was the stuff they have financial incentive to get plays on that I skipped the day before and "might be in the mood for now".
This alone drove me back to my local music library.
I would rather dislike a song and have it recommended in a "How about now" playlist to determine if I actually hate it or if it was a mood in the moment.
I used to track “skip counts” in iTunes and would review the most skipped songs every month or so and determine if they needed to be reduced in star count.
It would be nice if when you skipped a song it would do a soft pop up or something to ask why you skipped it. You could ignore it most of the time but if you felt strongly about the recommendation then you could at least vent your frustration on the "I don't like this song" button.
I think the main issue here is, is that users feel a bit powerless to influence the algorithm with thier dislikes as much as thier likes. Even though a song skip may be functionally similar to the dislike button, the user has no "haptic feedback", for lack of better term, when they really feel the need to have their negative opinion on the song heard by the algorithm.
I think most people's gripes with the nature of these recommendation algorithms deciding things, centre around the feeling that the algorithm doesn't listen to them and their opinion as much as it obeys other overriding trends. Giving them tangible and tactile options to deliver their opinions in hard and fast way gives them some more peace of mind that the algorithm is working for them, and not for some other entity.
Some songs have extremely long shelf life and others are extremely short. For instance, an "adult contemporary" station could probably get away with playing Elton John's "Tiny Dancer", a 49-year old song, without anyone thinking anything is weird.
More popular songs of that year such as those by Roberta Flack or Gilbert O'Sullivan would not get the same non-reaction
Some songs have even longer shelf life that are associated with real world things like birthdays, holidays, seasons, etc. It's pretty common to hear a set of Christmas music that was literally recorded during WW2 with everyone's approval.
Some songs grow on people, others grow tired quickly. The classic example is novelty songs that specify a dance such as the cover of The Birdie Song by The Tweets or Black Lace's Agadoo, which reached impressive popularity and then were promptly forgotten forever. Ones that you may be familiar with such as Rick Martin's Macarena, probably gave you a headache just thinking about it.
But not all. Chubby Checker's "The Twist", a song in this category of instructional dance pop music, has escaped the ban hammer of time.
But overall the pattern of memory holing proscribed dance songs is robust, even for songs that developed a dance without actually calling it out, such as "Achy Beaky Heart".
Also there's no asymptotic drop after release date. Some songs that are popular now and symbolic of an era weren't as popular when they were new and some have second lives when featured in say a television show, video game, or covered by a more contemporary artist. Every few years a new version of Gershwin's "Summertime" seems to come out followed by renewed interest in previous versions by people like Billie Holiday, Janis Joplin and Ella Fitzgerald. Should Ella Fitzgerald albums be recommended to people for the next 18 months now? Probably not the right way to interpret those results.
There's an exogenous contextual reason for such things and those have to be accommodated for
It's completely non-trivial and a simple model of skips and likes without sophistication behind it will dramatically fail to be anything other than an irritation
That difference is easily captured by the cases where you don't skip that track. If you have listened to a track two times and on the third case skip it, then that's "I don't feel like this now"; if you have been offered that track twice and skipped it both times immediately, then you probably hate this.
Or I just am not in the mood again. If I do not like something I want a way to tell the engine that and not be afraid of skipping my favorite songs because I want to listen to them at another time.
I think alogrithms are great but feel really frustrated and helpless because it somehow became impossible to explicilty give it signals or tweak it. It's like living together with someone who always tries to guess your needs but you are not allowed to talk to them. That's just a broken system.
I often leave my computer playing music, and step away for 15+ minutes to have a conversation. So "you have listened to a track two times" may be a false indication of "like".
Surely they have some context as to what "now" means?
I read that YouTube Music recommends different music depending on time of day, whether I'm at work / home / in the car, and even takes the weather into account. I'd be surprised if Spotify didn't have some context awareness as well.
I haven't noticed that Spotify would do anything like that. Instead they're pushing their podcasts and curated playlists. To be honest, I've thought that they're more like banner ads on websites rather an attempt at custom recommendation.
I recently got super into the band Squid. But I hated them the first time I heard them. It was because I was depressed and looking for more music like Black Midi-- Black Country New Road came up and was perfect. Squid came up and made me want to punch my speakers.
If they have enough data to predict my mood to that extent then I would like to hire them as my therapist.
Same! Started with Squid and Spotify took me to Black Midi, Yard Act, Dry Cleaning, all of whom I'd skipped in the past because I just didn't get it, now I'm obsessed. Some music just defies understanding on a first lesson.
it's not perfect, but ytm does what gp says. "You often listen to X in the morning" can be helpful even if it doesn't know about personal events in your life
No, I often have fear of skipping because I think it might teach the algos I don't like it, when it's just not what I want to listen to now.
Ideally, they should let me like, dislike, skip, hate, completely block artists, and allow me to like multiple times, to teach them the ones I like over and over from the ones I like a little.
There are 3 artists that Spotify continually play to me and I preemptively will fast forward them even during the crossover play because I dislike them so much. I’ve submitted requests before to have a “don’t play me this artist” feature. I don’t know why this is so hard for them.
Youtube for me, fixates on a couple of videos-- as in it recommends them every single time I use it-- one is a Marques Brown retrospective on the Gameboy, and one is the TYT (news outlet), story about a woman who had her face bitten off by an ape and is at least 8 years old.
I don't know why these show up in my recommendations every single day. I will never watch them.
Deezer have that option. When you're listening to something you don't like you can click on a little frowny face, then they will ask you if you want to never hear this song again or the artist.
It's neat.
Deezer has added a "don't recommend this song again" button. I used a couple of times only but I feel that my recommendations have been indeed improved.
Before, I had to skip the songs that I did not like, and Deezer was keep putting them back in my 'Flow' a few days later. That was pretty annoying.
An option to hide all podcasts would significantly improve spotify's recommendations. I don't listen to podcasts (though I have accidentally clicked on one, when a podcast interviewed a musician I like... blech). Why is my screen filled with podcasts multiple times per day? I like the music recommendations, "so and so artist radio," etc., but they make me hunt for them.
Also, while I like a broad variety of genres, I only like listening to one at a time. I don't want a rap mix to be invaded by a Bach sonata. And yet...
Why Spotify plasters your home page with Podcasts:
Short answer is $$$$.
Longer answer is:
Spotify must pay royalties for each song played. Imagine if there was a completely free (for Spotify) form of content that filled users ears for hours, thus removing the need for Spotify to pay royalties. Ahem podcasts. Now imagine if Spotify started injecting ads into said media form to grow their revenue beyond subscriptions. Again, podcasts. So now, you have a very long-form content that both saves you royalty $ and drives new revenue. QED. Podcasts will continue to be plastered all over your recommendations, be top search results, etc, until the above stops being true.
I think the more likely answer is that podcasts can be produced with exclusivity deals while songs can not.
Spotify is large because they were first and because apple/google music suck. But eventually apple and google will stop sucking and users will drain from Spotify rapidly unless Spotify can create content to keep users in.
Spotify is in the position of Firefox 15 years ago right now. Eventually the built in apps will take over.
Selling a burger is inhernelty profitable for McD, they sell it for more than they spend on manufacturing and shipping and serving it. Each new burger sold adds more profit.
Serving music is unprofitable for Spotify. They collect your monthly subscription fee, then every additional song play makes Spotify lose money. They don't want to have zero song plays since then nobody would subscribe, but their goal is sell the profitable thing (subscriptions) while minimizing the unprofitable thing (song plays).
Just to add to this restaurant based allegory, Spotify is like an all you can eat buffet that tries to serve out lots of sodas so you get bloated and don’t eat the expensive stuff they have
> their goal is [...] minimizing the unprofitable thing (song plays).
If that's the case, how do you explain those two features :
- the repeat button
- the "automatically play similar songs" option
In the first case, since I don't know how it works, maybe they have to pay only one time for a song per user listening to it during a period (say a month). But I doubt it.
In the second case, it's Spotify explicitly saying : "here are songs you don't intended to play but that we picked automatically and are playing to you".
If you look at Netflix, sure they have the feature that automatically launch the next episode. Or they try weird stuff like live or play anything... But they also have the "Are you still watching ?" feature, to make sure that they don't display content to an empty room.
Spotify doesn't have that, it can just play songs indefinitely without any human interaction.
Well...yes, not necessarily fundamental, but it's the same class of problem cinemas and restaurants have (to pick two). What do cinemas mainly make money from? What do restaurants mainly make money from?
Yes, that seems to be true (and is that % you've guessed maybe too low? Maybe far too low?). Even with that though, it's extraordinarily fine margins -- w/r/t the businesses that I mentioned, the majority of the income comes from those value-adds, if they weren't there it would generally be difficult for the businesses to survive financially. That's where I was coming from.
To me, Spotify seems to be using podcasts in a similar way. I assume it's because the central business model is unsustainable when combined with investor pressure; they can't just focus on core product because they're burning too much of other people's money in an attempt to outcompete everyone else
I'm sure it boils down to money ultimately, but it can't be the way you suggest here.
The thing is that Spotify does not pay per play! The royalties lobby love to give the impression that they do, because it makes it look like Spotify is fleecing them.
Spotify pays percentages of what it itself collects in subscription fees. If a record company owned 10% of everything that was listened to on Spotify this month, they would make _the same_, regardless of how many absolute seconds their stuff was listened to.
So, more listening to podcasts does not mean Spotify has to pay out less. How much they have to pay out in total is fixed as a share of their subscription (and ad) revenue anyway, in multi-year, industry wide contracts with copyright owners.
There are ways Spotify could circumvent this, such as promoting content they covertly owned themselves, or content whose owners gave them kickbacks of some sort. There's some indication they do such shady things. But podcasts don't change this equation much.
I think Spotify's promotion of podcasts is simply good old fashioned loss-leading monopoly building. They're hoping that Spotify will become where listeners go for podcasts since that's where all the podcasts are, and also the place podcasters go because that's where all the listeners are.
That is a great point about loss-leading a future monopoly and of course a factor.
This isn't a hill I will die on by any means, but if you read Spotify's write up on royalties[0], they pay out based on stream share of the overall platform, on a monthly basis. E.g. If Columbia Records gets 10% of streams for a month, they get 10% of the pool of $ Spotify distributes. Now, like you said they likely have some shady practices - I would imagine Spotify has an incentive to create music like study and sleep beats themselves as those playlists get hit for 8 hrs at a time and it doesn't really matter who created the beat as long as it helps you study or sleep.
They do not indicate in [0] that podcasts are excluded from stream share. Even if they aren't included in stream share now, I'd imagine long term they very much intend for podcasts and music to be lumped into the same stream share model to drive payouts down.
You aren't wrong, but you would think they would then create an excellent podcast player, yet they can't even get simple things like the order of the episodes correctly, and I still haven't figured out how to setup a next queue.
Not to mention that I might listen to podcasts at home and one the way to work, but at work I won't want to listen to anything spoken, but half the time I end up accidentally starting the podcast anyway. That now means I am not using Spotify for podcasts.
You’re probably right. But then again: who cares about Spotify making money? I want to listen to music and not optimize the bottom line of the Company.
Spotify dynamically injects ads into podcasts. I was listening to an episode of the Conan O'Brien podcast from 2018 and got an advertisement to be safe from Covid by enjoying an ice cold Miller Lite at home.
It was extremely unsettling until I realized what they were doing.
They replace the ad breaks that would normally be in a podcast. (Like when the hosts say "we're going to take a quick break to talk about our sponsors for this episode"). It's not an unskippable ad like you get when listening to music using the free tier. It's inserted directly into the audio stream.
Edit: I guess it's possible the Conan podcast is doing that somehow and not Spotify, but I've never had something like that happen when using the Apple podcast app.
Are you certain it was Spotify that did that? Unless you downloaded the episode in 2018, it could have easily been the Conan podcast. Podcast episodes aren't immutable, they're just a url. I've seen podcasts that update the ads in their back catalogue to whoever is paying them at the time the episode is downloaded.
I've also noticed some location specific ads, which isn't that surprising if you think about. There's nothing stopping them from serving you a different mp3 file depending on your IP geolocation.
When I listen through the apple podcast app I get ads that are clearly from 2018 though. Like for events that are long gone and over. Ads that don't match the year of the episode have only ever happened to me in spotify.
> Spotify Podcast Ads are powered by Streaming Ad Insertion (SAI), which leverages streaming to deliver Spotify’s full digital suite of planning, reporting, and measurement capabilities. Spotify Podcast Ads offer the intimacy and quality of traditional podcast ads with the precision and transparency of modern-day digital marketing.
Seriously. I listen to podcasts, but I'm not going to do it through Spotify, who's working to build a walled garden around a traditionally open media. I'm also not interested in Joe Rogan, which they _constantly_ plaster my front page with.
I did try a Spotify podcast once. It was on my recommended list and was called daily dad jokes or something. Figured it was worth a quick laugh. Well it turned out to be a bot podcast. They set up a bot to rip jokes from Reddit, push them through TTS, and dump it into a Spotify podcast.
No thanks.
Meanwhile, Apple Podcasts, my go to, works great, doesn't spam me, and even added a feature where you can pay for a no-ads version of a podcast. Worked seemlessly.
I rarely listen to podcasts but was going to try and listen to a specific one Joe Rogan did recently. After listening for a few minutes, an ad came on. I pay for spotify, why am I listening to an ad?
Anyway, I waited like 90 seconds and he came back on. Withing about 15 minutes, I had two more ads come on and they were 90 & 120 seconds each. After the second ad played, the podcast didn't start. Fiddling with it caused the podcast to start over from the beginning. When I tried to seek to the last place I was, it played an ad immediately. Seriously unbelievable.
I gave up and will never attempt to listen to an ad supported podcast on Spotify again.
Because Spotify doesn’t pay anything to the podcast producers. So podcasts run their own ads. (Well, some do. Others live off donations or offer a way to pay them)
I don't usually overreact too strongly to big tech making dumb decisions like these, but Spotify's podcast pushing actually did drive me away from the platform.
I beg Spotify to think Logically about it. There is a limited amount of screen real estate available on any display, but especially phones. Q.e.d: pushing podcast-related content actually hurts the music listening experience. Conversely, pushing music content hurts the podcast listening experience. This is (mostly) inarguable; any pixel dedicated to an interface element related to podcast content is a pixel which cannot display music content; its a zero sum game.
I say "mostly" because; there are people who I'm sure love Spotify Podcasts, and having both avenues within one app is a net win. I'd be willing to accept a toggle in settings which could "focus" the app Between Music <> Music + Podcasts <> Podcasts. I don't think that's unreasonable, and I also don't feel it would be unreasonable for it to default to Music + Podcasts.
Though it brings up an interesting point: Imagine the experience of someone who does primarily come to Spotify for podcasts. Its among the worst podcast apps in the history of podcast apps! Its littered with music! That's a horrible experience!
The ironic part is, Spotify is probably happy to lose me as a customer. I'm a "Music power user" if there were such a thing. They may end up paying more in royalties for the music I listen to than I pay them, and I can't say I've listened to more than a half-dozen podcasts. "Show me the incentives, and I'll show you the outcomes": Spotify is not incentivized to build an app that benefits people who listen to a lot of music. Their bread and butter is people who listen to a bit of music and podcasts; just enough to keep them paying each month. So, I don't lose too much sleep over their slow decent into mediocrity; I'm far more concerned about the unfortunate reality that there are no longer any great options in this space, for people like me.
You’re probably right but I have yet to meet anyone who loves podcasts in Spotify. The two groups I have encountered who use it are those who never listened to podcasts at all before so don’t know any other way, and people who begrudgingly use it because some podcast they like went exclusive there. Which I guess are both good for Spotify but it puts them in a weaker position than if people actually did truly like the experience.
It has been years since I've tried Pandora: Back when I tried it, they only let you skip a number of songs in a short time and often played things I didn't care for. Lots of slightly obscure songs weren't available. It might be better for more popular music or have improved in the last decade, I don't know. I started using Spotify.
And still now as then: It is only available in the US. I no longer live in the US.
> they only let you skip a number of songs in a short time and often played things I didn't care for.
If you aren't in the US, then it won't work, but I create multiple stations and can switch station if the music isn't good. I can't remember it ever not being good though. I use the like button to train it.
> Lots of slightly obscure songs weren't available.
If I'm looking for a specific song, I usually go to YouTube. Most of what I listen to is pretty obscure, but it might depend on the genres.
I have never listened to a podcast on Spotify and I still have them on my home screen, so I think that it's hardcoded, not a generated recommendation.
The probably autogenerated daily mixes have been surprisingly non-bad for me. Nothing like rap mix invaded by Bach, but the "classic rock" mix sometimes has Ghost that doesn't really sound that out of place.
My guess is that they don't have to pay rights for the podcasts, so for them it's a win/win if you spend your attention on their app listening to free content.
I was using Spotify for podcasts because they were there, but then my home feed got dominated by them, and they occasionally get queued up and giving me a mix of podcasts and music, which I don’t want.
I started migrating to Apple Podcasts so I can context switch more easily.
I'm really disappointed how Spotify is buying several big podcasts and moving to their platform exclusively.
I tried to listen to a Science Vs episode the other day, and now my Spotify is almost completely filled with podcasts recommendation. Plus, the experience is still far from specialized podcast apps.
The result: I'll probably stop following Science Vs (and any other podcast that moves exclusively to Spotify).
They could, at least, have a separate Spotify Podcast app so things wouldn't be mixed (kind of like Wealthsimple has separate apps for Investing and Trading).
I'm still sad Spotify bought Gimlet and apparently will do (if not already) this to all their podcasts.
I listened to one episode of "Call Her Daddy" because I saw it ranked as one of the most-listened podcasts out there and Spotify will not let go putting it front and center on my home screen every day.
So basically they’re developing a product marketed to streaming platforms to identify what’s “more attractive” to consumers. The algorithms are still optimized for increasing sales and engagement, not improving recommendations (for the user).
That’s exactly why I’m unhappy with Spotify lately. I feel I’m being sold a bunch of corporate portfolios on what’s currently in vogue, and not just artistically but politically, with playlists like this-gender-race supporting this-cause. I actually just want to listen to music.
I still use it but stumble my way through looking at related artists while avoiding playlists and recommendations.
On top of that, if you listen to a wide range of genres the attempt to shoehorn your history into 6 Daily Mixes yields some comical results. Like Doobie Brothers followed by Nirvana.
Give me a home screen with 12 or more Daily Mixes that segment my listening behavior at a finer resolution, and I'd be a lot happier with the service.
I understand why all the other playlists exist, but I generally have an idea of exactly what I'm trying to listen to, so these low effort curated playlists are pretty useless for my listening style.
Well for me at least, I listen to music depending on mood. It's not generally that I dislike mixing, quite the opposite actually. But when I'm in the mood for metalcore, I'm not in the mood for happy hardcore. And when I'm looking for something quick, I don't want a slow song mixed in.
I like the idea of mixing genres, but Spotify seems to totally miss on what aspects I want mixed.
That example might be OK, but my daily mixes include "Weird Al, Nerdcore Comedy, and also Radiohead" and "60s/70s/80s Rock and also Broadway Show Tunes". The transitions are very bizarre.
The local classic rock radio station I listened to growing up has continued to slowly expand what they consider "classic"; whenever I go back home, it's always interesting to hear stuff like grunge and some metal (like certain Metallica songs). Hearing a Nirvana song right after the Doobie Brothers is exactly the type of thing I've probably heard before from them!
I agree. I love the wider scope of Spotify’s mixes. If I wanted a narrow scope then I’d just have created the playlist myself like the old days (or just thrown an album on). The reason I use Spotify mixes is for a variety within an approximate mood. And I’ve discovered so many good news tunes and artists through their mixes.
That all said, I do wish I could turn off their podcast recommendations. I never listen to podcasts and worse yet they keep shoving that same comedians is absolutely hate (and there aren’t many comedians I dislike; which just goes to show how far off the mark their podcast recommendations are)
Then you can simply find a song that matches what you're exactly wanting to listen to and start the "song radio" from there. For me the problem is exactly the contrary, I can't find enough diversity in the daily mixes, it's mostly all songs I've either explicitly "liked" or heard a couple times before.
Diversity in daily mixes is an issue for sure. I do use the song radio feature but find it's hit or miss - they usually start off strong, but seem to lose the thread at a certain point.
It's a fine balance between existing liked songs and expanding within sub-genres, but I have at least noticed the recommendations improving over the past few years.
I suspect it would help to port over my entire pre-Spotify music library into Spotify to provide a bit more data, my current library is all post-Spotify so it fails to capture the breadth of my music taste. I've just never gotten around to it.
I've considered getting a spotify family account, using separate accounts for major genres and one for browsing. I have a browsing profile for Netflix so I can freely explore without messing up the suggestions.
For me, I listen to a lot of 40s, 50 - 60s lounge / exotica, early to mid 90s hip hop, 80s metal, and the standard indie stuff... then I have a bunch of chillwave and synthwave stuff that throws another wrench in the mix. The daily mixes I get are a total mess, much like yours.
The genre-specific mixes they make are pretty decent, but discovery is low.
I have a separate account just for Amazon Echo because I don't want my kid's selections to influence my main account suggestions.
I also have my own account for the car, where explicit songs are disallowed. This allows me to listen to the music I like, but it avoid explicit songs for when my kids are in the car and that setting doesn't affect my main account.
That's the exact reason I switched to YouTube Music.
I remember even about 10 years ago, last.fm's algorithm on bringing songs I would enjoy basing on previously listened/liked songs was far more accurate than Spotify's today.
YouTube makes recommendations around engagement metrics only (1 political video gets you Fox News recommendations for years), spotify still gives me plenty of small bands - I think if you’re listening to very popular music you’re screwed either ways
I was at a conference the other week and Spotify had a Keynote. They talked about the tradeoff between playing "diverse songs" and "consistent songs". It is a hard problem to solve.
When you start your listening session they try and predict how long you are going going listen (based on your past history and time of day). If you are probably going to listen for a while, they are more risky and might play something "different". Playing different stuff is risky (short term) because you MIGHT not like it. Playing the same stuff is safe (short term) because they know you will like it - BUT people will eventually go searching for something new, so they have to risk diversity eventually.
Exactly. There's no reason the "personlized" Daily Mixes can't be built/labeled to indicate "acaccuracy" rate. It annoys me when I'm in the mood for new or different - which is 60% of the time - and all the new Daily Mixes feel like the day / week before.
I'd love a personalized playlist titled "Curveballs" that contined things different and/or challenging.
I get mostly small bands in Spotify and I worry that Spotify is actually bias towards them. I assume the royalties are cheaper for smaller bands and that may factor into recommendations.
Weird, I switched to Spotify once Google Play Music (or whatever silly name it had when Google ate songza) became YouTube Music because I found it such a poor experience.
Perhaps I was missing something but the change def did not improve the recommendations - it made them drastically worse.
In my experience, Spotify's recommendations are good for a few months, and then stick in a rut at some point for reasons I don't understand. So you're probably in that nice honeymoon phase where it's actually allowing you to discover new things instead of surfacing the same 20 artists over and over and over again.
For me Spotify was discovering good new music for years before getting “stuck” recommending the same artists over and over again last year. I do mark them as “I dont like this song” but it still will recommend them later. I think it’s time to reset and start over.
Does the algorithm of YouTube Music behave similar to standard YouTube? YouTube (not Music) basically always recommends the same tracks in the same order and within the same genre bubble. It is hard to discover anything new which makes me not want to try YouTube Music.
My experience is the algorithm is a bit different. I have not been on the platform for long, but my recommendations have been great. I've also been listening to music on the same youtube account for 10+ years, so I assume they have alot of data.
This was my experience with YouTube music - no matter what genre station I started off with, it eventually settled back onto the same small number of currently-trending songs. I get much more diverse recommendations from Spotify.
I just switched to youtube music, its leagues better than spotify. YouTube music seems to have a pretty solid recommendation algorithm, and I frequently find music more in tune with my tastes there than on spotify. Honestly, I would not mind seeing spotify disappear.
I'm thinking of going the other way, I just dislike how YT Music doesn't have some small feature like saving my queue to a playlist. But perhaps I should hold out.
Fwiw, I was shocked how much better YouTube music was than Spotify. I turned on the trial on a whim, and now I actually miss it (it expired a few days ago).
It was so nice that I’m seriously considering just turning off Spotify. It’s sort of interesting to analyze why we don’t —- for me, it’s become unconscious habit to reach for Spotify and not anything else. Plus a lot of other stuff integrates well with it.
(What if… what if we can use both? Mind asplode, it’s not a decision.)
Its funny how much better Googles side show product is. Shows that the internal technology is truly advanced and capable of swiping away another company at the drop of a hat.
I'm just trying it out now based on the recommendations in this thread. When you start it asks you to pick some favorite artists. The first few rows were clearly based on artists that I've watched recently on YouTube, so it's pulling in history (I mean...no surprise).
Then I scrolled down a bit b/c I wanted to give it a strong signal of what I liked. I found an artist, clicked it, and noticed the recommendations below changed immediately afterwards.
So then I scrolled some more (because there were still 95% misses), found one I liked, scrolled to see the next row then clicked on the artist I liked above to see if it indeed changed.
It did. But not only that. I love every artist on the following row. Then it quickly diffuses back to noise, but holy cow that was a bit of a spine tingler lol.
Anything that can be exploited by the user for self-exploration and discovery is being removed - for the purpose of serving content that generates more revenue, I assume.. At first it was subtle, but the gloves came off with the recent UI overhaul.
Playlist search result page is just an endless grid of images and truncated names. For the playlist duration, description, number of songs, follower count, etc. you have to actually open each individual playlist. Good luck finding what you were looking for.
More and more Spotify-fabricated content is being pushed. Most of which contains the same limited selection of songs that Spotify keeps feeding you over and over anyway.
Podcasts aren't my thing, Spotify wants me to listen to them really badly though. Majority of the ones they're suggesting I'm not at all interested in, and sometimes some of the podcasts they're advertising seem to contain some pretty disturbing content. On a sidenote: I don't know who he is, or what he does, but I hate Joe Rogan and Spotify is to blame for it.
There is a setting hidden under advanced that is supposed to make Spotify stop messing with the shuffle functionality. It is labeled "Allow smooth transitions between songs in a playlist" vague huh, it's also placed directly underneath the song crossfade slider. I'm fully convinced that this was done on purpose. Also this setting seems to do precisely nothing at all, so I'm not sure why they even went through all the effort.
Shuffle is not random. If this is so on purpose, that purpose does not involve happy users. Else perhaps their devs are afraid of touching some jank script that might be holding it together.
Edit:
Almost forgot about the new artist's pages! They used to consist of a long list of all songs grouped by album. This was far too convenient for us users, so with the redesign they simply removed the lists of songs leaving only a grid of albums, forcing you to go into each individual album to find a specific song and play it play it.
After many complaints they implemented something vaguely resembling what we had before, but with such odd UX that it must be sabotaged on purpose again. But of course, adding this overview back to the artist page was out of the question. Instead what they implemented as the only way to access this, and I kid you not, is a plain text link in the most random place ever.
No one is going to use this feature if they don't know it exists. All this just to get a reason for removing it that is spinnable. Machiavelli would have been proud.
What’s funny is that I used to love listening to the Joe Rogan podcast and hate Spotify just as much, because I tried to listen to his podcast and somehow ended up listening to about TEN MINUTES of ads and the podcast NEVER started playing. I finally uninstalled Spotify and haven’t listened to his podcast since, sorry. It’s mind boggling that Spotify could drop the ball so hard, as ostensibly they were trying to funnel people like me into their platform, and whiffed in an absolutely astounding manner while also alienating people like you who already use Spotify.
> I feel I’m being sold a bunch of corporate portfolios on what’s currently in vogue, and not just artistically but politically, with playlists like this-gender-race supporting this-cause.
I feel the same way. It's not just music either. I get this feeling every time I try to consume anything. Everything is just so fake. Like it was made just to push some silly agenda.
"Recommendations" are ads in disguise. I already block them on YouTube. Wish I could block them everywhere.
Yeah, this is the exact reason I switched to Apple Music even though I'm on Android, since their playlists (for the most part) seem to actually be made based on what they think will be interesting for the listeners, not what they got paid to promote. I might be wrong though and just getting played.
similar experience here, after 12 years with spotify I had enough of the confusing UI and poor recommendations. They literally know all the music I like and still I don’t discover enough new music as I did just listening to the car radio. Bought into Apple One and will see how that goes, I just need to migrate some playlists.
whoa thanks for the heads-up! I've always wanted to try other platforms but I've thought it impossible since I have so much data in Spotify. Any gotchas here?
You will have to share access to your data, so expect them to sniff a lot about you and your friends from Spotify. Highly recommended to remove access once the migration is complete.
The free version transfers only 1000 tracks, about 1-2 songs per second, and some might be missing in the destination, e.g. when moving from Spotify to Apple.
Favorite artists cannot be transferred to Apple Music.
I use Apple Music because it works well with the rest of the ecosystem. But the official playlists just seem to resurface what’s already popular, at least for dance, electronic and hip-hop. Whereas Spotify introduced me to new music. Maybe it depends on what genres you listen to?
I've never used Spotify or any other recommendation service. Music is like food: it's far too important too substitute with junk. I won't eat Subway, I won't listen to auto-generated recommendations. I browse (and support) rateyourmusic.com, I use the last.fm API (to find out what my neighbors are listening to) and I listen to music for free on YouTube before I buy it. I also heavily use tags on my purchased music so I can easily put together a playlist matching my mood.
Disagree with the premise - you don’t have to sacrifice productivity to put time into finding good music. For one, you don’t have to do your music research during working hours. But even if you do, it doesn’t mean you’re trading off productivity in order to do it.
you don’t have to do your music research during working hours. But even if you do, it doesn’t mean you’re trading off productivity in order to do it.
Trying to find music when you could be focusing is by definition, trading off productivity.
I’d rather have an algorithm dictate what songs I want to listen to (in order to focus) than spend an hour wading through junk to find something i like before I start coding.
I want a service where I can upload my own files and easily access them from a player interface in the browser, mobile, etc.
I want the ability to rate music across multiple user-configurable dimensions. Add tags. Create smart playlists that interpolate between these.
I want to be able to pay a fee to subscribe to music discovery, then be able to mix these with my own library. If I really like a track, I'd like to buy it and add it to my collection.
I want an open API so desktop apps can be written to use it. Also, let me export my annotations and music library on demand.
Music for power users. Don't give me a single button. Give me hundreds of them.
Check out Navidrome [0]. It's the closest one that I've found. It supports the Subsonic API so there are plenty of mobile apps and probably some desktop ones that work with it. I use play:Sub on iOS.
Unless I'm mistaken, this doesn't fulfill the requirement:
> I want the ability to rate music across multiple user-configurable dimensions. Add tags. Create smart playlists that interpolate between these.
I'd actually pay for a 3rd party metadata service that doesn't actually provide the music at all, but just let's me tag and rate some across all music streaming services. I've even thought about building that (simply for myself to begin with). I want ratings, instrument tags, mood tags etc. Let me search for songs with 'piano + synth + dreamy + weird' instead of throwing some stupid recommendation my way. And use those tags to find similar tracks across genres and decades of time, instead of just saying "Nirvana and Pearl Jam must be the same because they're early 90s Seattle bands".
I use Airsonic right now, it is basically Jellyfin for a music collection. I use both of these as reliable alternative to Netflix/.../Spotify (where ... is a plethora of other video services such as Disney+).
3. More modern webui (though I recently found a good desktop subsonic client, sonixd which somewhat negates this)
Also, I haven't used the airsonic fork, but I was using subsonic before switching to navidrome
I found subsonic to be rather... unreliable. once in a while the database would randomly become corrupted and I'd have to delete the database files and start over. I haven't had any such problems with navidrome, it's been rock solid.
- Upload and download your own stuff if you want to (marketed as iCloud Music Library)
- Works offline
- Discovery services available
- API exists but mostly used to implement web players for some reason, works fine in desktop apps too, on top of that the current state of your music library is always available as an XML file even when you don't use the API at all.
It's fingerprint matching, and yeah it's poorly implemented. Most recent complaints I've seen on this were for the fan made explicit version of Kanye's Donda. It was basically impossible to upload since it would just get matched to the clean version.
Matching is optional. If a song cannot be matched, your own copy gets uploaded instead to your private iCloud library.
Edit: well, it's a bit nuanced of course, you can not match and not sync or match and sync but you can't mix and match that configuration. So it's either sync with matching when possible or no syncing.
I have a lot of rare stuff. Demos, live albums (grateful Dead, dmb), live captures of daft punk at Coachella, underground hip hop mixtapes, CDrips of local punk and Ska bands from the 90s
I haven't had an active subscription for a while (when iTunes was the desktop app instead of Music being the desktop app) but I distinctly remember being able to set metadata in the Info panel on a song or multiple at once that prevented fingerprint matching.
But as the name already implies, that one preferentially tries to match your files to the ones already available in Apple's music catalogue, with file upload only serving as a fallback if it can't find any matches.
And from what I've heard, the fingerprinting algorithm is fuzzy enough that it will often match songs/song versions that are very similar, but not actually identical, like censored/uncensored lyrics, different masterings, differing fade ins/outs, alternate takes and live versions, etc. etc.
Oh interesting – somehow in my mind I've mainly associated this phenomenon with Apple, but of course in a way this make sense and saving storage space that way is a tempting target for that kind of service I guess.
It makes me curious though how the accuracy vs. deduplication efficiency trade-off looks like in practice: How much storage is Apple saving with their current settings, and how much deduplication would they lose if they made their audio fingerprinting more accurate, up to a level where even audio buffs would stop complaining
I looked for that when Play Music got shuttered but could not find a satisfactory solution. I even paid for one iOS app but it wanted access to my entire drive, and maybe some other unnecessary permissions.. so hell no. I should be able pick one folder and that's it.
I guess I could have made a separate Google account just for music.
I bought a jelly pro (miniscule phone), rooted it, added some automation to autoload a music player on boot and activate airplane mode. I added a 256gb memory card with a lot of tunes. It's now my mp3 player. When I deactivate airplane mode it scrobbles my played tracks and 15 minutes later it automatically reactivates airplane mode unless the phone is charging, in which case it's available for wireless music sync from MusicBee. It also powers itself off after 30 minutes of being idle. Best damn mp3 player I've ever had.
My service, Astiga, does this. You can upload your files to any supported cloud storage service, pair it with Astiga, then play either via the Web, our apps or any other client that supports Subsonic.
funkwhale has the web interface, the subsonic api (dunno how well that works i dont use it), you can create your own "radios" based on genre and artist
The fact that Spotify doesn't optimise for discovery and recommendations is why you use physical media which has absolutely no mechanism for discovery and recommendation?
It’s fascinating to hear this feedback on Spotify because I’ve never used it this way. I don’t let it guide anything. I just use it as a music repository and I pick the albums and make my own playlists.
Do others generally find that auto play (or whatever it’s called) works well? Or does it just feel like payola radio?
"Discover Weekly" tends to be one of my primary sources of new content discovery. I tend to listen to a significant amount of Death Metal, Doom Metal, Folk Metal, German metal and rock, random music in languages I don't understand because the sound is cool to me, and various other never-been-pop subgenres. Discover Weekly has been pretty on point for me to find new and interesting stuff in a way that hasn't felt like them pushing a message or some corporate catalog.
I don't tend to listen to the genres that are full of artists who are trying to push politics through their music (at least that I've consciously recognized) (except maybe System of a Down). Not because I'm necessarily against their messages, it just the sets haven't overlapped much for me at this point. It could also be that music isn't much about lyrics for me, it's about if it's something that sounds good to me.
I have a bunch of playlists and saved albums, but I do listen to discover weekly in the first few days of the week. Sometimes it's meh and I just go choose what I want to listen to, sometimes it's really good and it's on loop through the week.
Their "Daily Mix" playlists seem to be 90% stuff I've clicked "like" on in the past, so I listen to those as well.
Why would you let a streaming service choose what you want to listen too or a premade playlist by someone else? Then you might as well just listen to the radio. All these on any service are always rubbish. I make my own playlists and I only listen to them, sometimes I search others for some inspiration to see what songs I forgot etc, but most of them include a lot of trash so I make my own.
The only 'auto' feature I use, is my release radar playlist which I check every Friday to find new songs from Artists I like and then add those to my playlist titled for the current year.
I think it is sad that there isn’t a way to recognize the development of competence in music listening— with an achievement motivation. Like, mastering genres with a music collection. Aesthetic pleasure in pleasant recommendations without any principles makes me feel vacant after a time.
With respect, your comment illustrates the issue - a burden to reeducate people by shaping their culture. Music can make a statement, sure, but a world where people are force-fed curated playlists designed to mold them into some Standard Issue set of beliefs, this is a dystopian vision.
I think that people bristle at it in the same way that people used to bristle at having Christian-normative culture pushed on them. Not everyone enjoys cultural imperialism.
Sarcasm and belittlement are a terrible way to engage in conversation. You seem more interested in aggrandizing yourself than to actually make a point or bring some food for thought.
So basically they’re developing a product marketed to streaming platforms to identify what’s “more attractive” to consumers. The algorithms are still optimized for increasing sales and engagement, not improving recommendations (for the user).
It's possible that the recommendations are both good for users and good for corporate interests. They might not work for you, but for millions of Spotify users they seem to work. People listen to them a lot.
I listen to my recommended "Discover" playlists occasionally. They're decent. They include things I haven't heard and quite like. Maybe record labels are paying to be on them. Oh well.
I’ve never really understood what variations of the rejoinder “you are not the target user” are intended to accomplish, at least in conversations like this.
When discussing things like product strategy it makes some (more than a little) sense. But in a conversation about personal preference, what do you expect the reader to take away from it? “Oh okay, sorry, I didn’t realize I wasn’t meant to like this. I guess my opinion’s invalid.”
Who cares who the average user is, when someone is saying something doesn’t appeal to them? Is the sentiment some kind of scolding for not liking it? I sincerely don’t understand.
I think the remark is meant to address internet comments' tendency to jump from "this product doesn't meet my needs", to "consequently it is a bad / mismanaged product".
From the original comment: "The algorithms are still optimized for increasing sales and engagement, not improving recommendations (for the user)." That is an opinion about 'product strategy'. The answers, in this context, are confirming that 'not for the user' part. I find relevant to highlight that HN may not be the most representative crowd in this situation.
I do not use Spotify, nor I had for years. And I do not like the level of influence that all those algorithms have on the population decisions. So, it's not about protecting Spotify but an observation to try to add another point of view to the discussion.
I’ve never really understood what variations of the rejoinder “you are not the target user” are intended to accomplish, at least in conversations like this.
It's simply a reminder that when you work at scale you can't please everyone. Someone complaining that a feature doesn't work for them is not the same as saying it doesn't work.
On a site like HN the conversation is usually about the broader picture rather than individual complaints unless someone is responding directly to the CEO of a company. I think the CEO of Spotify posts here occasionally, so maybe he'll reply. The rest of us are talking about it in more general terms.
That’s just the appeal to the majority fallacy. People may just use Spotify because it’s free with ads and they have the hook of personal libraries to keep you stuck on the service as a paying member.
* "good fit"/"bad fit" button — I like a wide variety of music, but it needs to be appropriate to context. If I start a radio from a song, I'd like to teach it to tailor the suggested songs better but that doesn't mean I dislike the songs it _is_ suggesting.
* Ability to give the social context — a band playing at a music festival will lean more towards hits in their back catalogue. At their own gig they may play some obscure stuff that die hard fans will really like. Similarly, what I'm listening to will be different if I'm having a party, friends over for dinner or on my own. On a family account, you should also be able to say who is listening & it should tailor to music that you might all enjoy.
* I get that they don't want to block artists/songs completely but they _should_ allow limiting how many times they suggest it per day. If I've listened to Everywhere by Fleetwood Mac on one playlist I probably don't want to hear it again an hour later on another playlist