How Spotify's Algorithm Works (From Its Creator)
ฝัง
- เผยแพร่เมื่อ 6 ก.ค. 2024
- Order THIRD EDITION of How to Make It in the New Music Business: book.aristake.com
Glenn McDonald was Spotify’s data alchemist and the creator of the music exploration site Every Noise at Once. He writes things for people about how humanity and technology co-exist, and things for computers about how to cope with not being human. He wrote a weekly music review column called The War Against Silence for ten years, tabulated the Village Voice’s Pazz & Jop music critics’ poll for several years, and was part of the music-intelligence start-up The Echo Nest, which was eventually acquired by Spotify.
He believes that music is the thing humans do best, and that bringing all the world’s music together online is one of the greatest cultural achievements of his lifetime. His book explaining why is being published by Canbury Press in 2024.
This week, Ari and Glenn McDonald discuss his role as a data alchemist and his work on the Every Noise at Once genre map. McDonald shares insights into the creation and maintenance of the Every Noise genre map, which categorizes over 6,000 genres and subgenres. He also discusses the evolution of Spotify playlists, from editorial to personalized, and the impact of algorithmic programming. They explore the impact of algorithmic recommendations on artists and fans, as well as the challenges of detecting fraud and bot attacks.
Chapters
00:00 Introduction and Background
08:30 Creating the Every Noise Genre Map
19:54 Personalized Playlists and Algorithmic Programming
32:25 Fans Also Like and its Evolution
37:06 The Challenges of Algorithmic Recommendations
41:30 The Limitations of Detecting Fraud
47:56 The Mystery of Sudden Streaming Spikes
01:00:19 Glenn McDonald's Book and Future Plans
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Edited and mixed by Ari Davids
Music by Brassroots District
Produced by the team at Ari’s Take
Oh wow - I know Glenn from his support of the chillwave / chillsynth genre and his support for my own music. A great dude. Excited to check out the book 👍
This looked promising but he didn't come to play. 😞
Incredible interview, loved learning and hearing about the backend and intent of the algorithms!
Yea!
Swear the Fans also like is full of some our personal friends because I have that issue as well , thanks for bringing that to light
I have a question, when running ads for my playlist on Spotify I realized something: I only pin locations in the US and there are times when I see not only the US but also countries like: France, Germany , you,... all tend to increase. So I don't know if Spotify's algorithm groups together countries with similar cultures or listening behaviors to recommend to listeners? Hope to hear your answer
quick question: If I'm an indie songwriter and my publisher is SongTrust and my distributor is Distrokid, how do I determine what percent of the DSP revenue goes to each party? For example, if Spotify will generate $0.003 per stream, how do I determine what percent of that 0.003/stream goes to my publisher and what percent goes to my distributor?
DSPs pay publishers and PROs directly the mechanical and performance royalties. All the money that the DSPs (Spotify, Apple Music, etc) pay DistroKid is only the master revenue. Publishing is about 20% of what master royalties are
Everynoise New Releases by Genre is/was essential to discovery as a gigging DJ. Spotify pls fix. :/
well Ari has a whopping 2.300 monthly listeners on spotify, so he's deffo the guy to take advice from, while the fans also like on spotify for smaller artists is absolutely trash.
I'm talking about the artists I manage.
And Phish has a whopping 400,000 monthly listeners on Spotify and they sold out 4 nights at the Sphere in minutes and are one of the most successful touring bands of all time. You're paying attention to the wrong metrics my friend.