Algorithmic recommendations and discoverability of French-language content on music platforms

This project examines the discoverability of francophone music content in the era of streaming, combining a qualitative study conducted with listeners in France and Québec with an experimental audit of Spotify’s recommendation algorithm. It explores how individuals encounter francophone music in their daily listening practices, and to what extent editorial or algorithmic recommendation tools truly shape this exposure.

The results show that platform recommendations are only one pathway among many: discovery relies primarily on musical socialization, peers, radio, and everyday listening contexts. The algorithmic analysis reveals no significant geographic bias, but does highlight a slight linguistic bias favoring English-language content, a pattern that becomes more pronounced when users re-listen to recommended tracks.

By shedding light on the sociotechnical mechanisms that govern the circulation of local works, the project helps deepen our understanding of the conditions shaping the visibility of francophone music and the contemporary challenges of cultural pluralism online.

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