Spotify, Passive Listening, and the Homogenization of Music
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The act of listening to music has changed and Spotify (and other music streaming services) know it. What used to be a laborious task involving taking out records, flipping tapes, or changing cd’s is now portable and at the listeners fingertips, wherever they may be. Listening to music is an activity you can do all day long: while you work, study, commute, etc.
When’s the last time you sat down and just listened to music without any accompanying task?
This is called passive listening. This is the predominant way of listening to music now. As opposed to being actively engaged analyzing lyrics, instrumentation, composition. The passive listener listens to music as a background activity to compliment the task they are focusing their attention on.
Spotify was created for the passive listener. Spotify founder Daniel Ek’s professed that his ambition, in his own words, is “to soundtrack every moment of your life.” And it can.
Creating these personalized playlists like “Discovery Weekly” where listeners are suggested new music each Friday comes from…
- Collaborative Filtering models (i.e. the ones that Last.fm originally used), which work by analyzing your behavior and others’ behavior.
- Natural Language Processing (NLP) models, which work by analyzing text.
- Audio models, which work by analyzing the raw audio tracks themselves.
Collaborative Filtering is the idea of suggesting artists and tracks based on other listeners’ listening patterns. If listener A and listener B have listened to the same artist as listener C then other tracks and artists that listeners A and B have listened to will be suggested to listener C.
Natural Language Processing (NLP)is the basic idea that Spotify crawls the web constantly, analyzing text from the web constantly looking for blog posts and other written texts about music to figure out what people are saying about specific artists and songs, what adjectives and language is frequently to describe the artists and which other artists and songs are also discussed alongside them.
For example, looking at my own band’s similar artists, many of them are friends of mine that I play shows with and are often mentioned in articles both about us and them.
Audio Models analyzes the raw audio of the tracks and further improves the accuracy its recommendations.
How does the algorithm contribute to passive listening and the homogenization of music?
Spotify allows passive listening through the recommendation of music and arranging them in a playlist. This way you aren’t actively seeking out a certain artist or new artists, but they are directly giving you algorithmically curated suggestions, which is very convenient. However, going back to mood playlists I previously mentioned, they, along with genre curated playlists, are one of Spotify’s most popular features, especially those under the ‘Chill’ category.
Writer Jenn Pelly describes these mood playlists as:
“…the purest distillation of its ambition to turn all music into emotional wallpaper. They’re also tied to what its algorithm manipulates best: mood and affect.”
These ‘playlists are populated by a genre dubbed Spotify core. Even if you’ve never heard of this term you’ve definitely come across it. It has a distinct sound. Think of Billie Eilish and other Theres minimalistic production, usually electronic, sometimes with ethereal female vocals singing some sort of dark lyrics. They also usually feature a pop drop, which is a softer version of the EDM drop, mainly in the chorus, which is proven satisfying to listeners
Here are a few examples:
Despite you never hearing of these artists, they have millions upon millions of streams. The popularity of this genre, that evokes a mood as opposed to active listening interest, can be traced back to the mood playlists and then the algorithm taking its course. If many of these style of artists are being listened to on a mood playlist, then similar artists will be recommended to listeners based on Collaborative Filtering and Raw Audio Models, increasing the popularity of this style of music. Then, in turn, more musicians and labels are churning out this easily digested genre of music further increasing its consumption. Spotify is even distributing it through their RISE program where they collaborate with “up and coming musicians” (usually already with millions of streams) to get in on the action.
The homogeny of this music works to Spotify’s advantage and is probably why the style on their mood playlists and even collaborate with Spotify Core artists with their RISE program. It’s easily to create a playlist that seamlessly goes together and in turn keeps listeners listening. Whether it’s a seamless chill out playlist or discover weekly it keeps Spotify soundtracking without the listener giving it a second thought. Listeners become a character in a movie, with a soundtrack in the background you can’t even hear. It’s just a mood.
