Algorithm-Based Music Recommendations

It’s no secret--when it comes to music, the internet really pays attention to you. Music definitely seems to reach its target audience quite easily nowadays and that’s thanks to one major component in today’s interweb: algorithms. Each music streaming platform uses different algorithms to help determine what kind of music each listener might like to listen to. 

Today’s most popular music platform with the best algorithm would be Spotify. In an article written by Sameer Balaganur, he breaks down how the streaming platform uses an AI to help with the organization and breakdown of music to each user. This AI helps with finding music and recommending songs based on what the user does with each song--skipping, repeating, etc. Spotify’s AI then recognizes all of these factors and helps create playlists with the users’ liked songs and add new songs that the listener might like. Spotify also comes with a browse tab that allows users to find new music outside of their tastes.

Apple music also does mirror the same features as Spotify; however, it also helps organize the different songs you already have downloaded onto your mobile device, which would normally be on iPhones.

Another music streaming platform that isn’t similar to Spotify or Apple music would be YouTube music. Similar to their videos, YouTube’s algorithm is based on multiple factors such as meta tags, watch times, categories, etc. This allows for playlists based on different types of music or new artists to show up on a listener's feed.

Data plays a huge part in algorithms, and although it seems a bit creepy for these streaming platforms to track the different sounds that you like, it does help with personalization and allows for more options to be available for the user.


Written by Romina Escano

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