In The Mood for a Vibe

My MA thesis is about the mythical term 'vibes' and how Spotify turns vague concepts like “vibes” and “mood” into something measurable and marketable. By combining cultural analysis with data from Spotify’s API, I show how mood-based playlists are constructed through both language and algorithmic patterns.

It argues that these playlists don’t just reflect emotions, but actively shape them, turning user feelings into data that can be categorized, predicted, and monetized. In doing so, Spotify positions itself as both a tastemaker and a system that subtly structures how we experience music and mood.