Research Paper

Research Paper

Nicola Mantelli

Abstract

This thesis investigates how Spotify's playlist ecosystem, particularly its algorithmic and edit orial playlists (New Music Friday and Today’s Top Hits) affects musical diversity and artist visibility. The study updates the basic framework of Aguiar and Waldfogel (2018) with 2025- relevant features, such as Discovery Mode and the AI-powered DJ, using a data-driven methodology. It assesses the degree of genre diversity and concentration in the most popular playlists on the platform using quantitative techniques such as Shannon Entropy and Gini Coefficient computations. The monetary benefit of playlist inclusion is measured by a case study analysis of LISA's song "Moonlit Floor," which estimates that its presence in Today's Top Hits has resulted in nearly 2.6 million more plays. The findings raise concerns regarding equitable exposure, which show that both editorial and algorithmic playlists have a modest concentration of genres and a higher concentration of artists. While algorithmic innovations promise personalization, they may reinforce existing commercial hierarchies. This study adds to the current conversation about platform dominance in music streaming by providing important information about the forces influencing music exposure, discovery, and industry dynamics in the digital age.

Publication Date

7-1-2025

Campus

Valencia (Spain) Campus

Research Paper

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