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Follow the algorithm : An exploratory investigation of music on YouTube

Author

Listed:
  • Massimo Airoldi

    (UNIMI - Università degli Studi di Milano = University of Milan)

  • Davide Beraldo

    (UvA - University of Amsterdam [Amsterdam] = Universiteit van Amsterdam)

  • Alessandro Gandini

    (Middlesex University)

Abstract

This article presents an exploratory study of the network of associations among 22,141 YouTube music videos retrieved by ‘following' the platform's recommender algorithm, which automatically suggests a list of ‘related videos' to the user in response to the video currently being viewed. As YouTube's recommendations are predominantly based on users' aggregated practices of sequential viewing, this study aims to inductively reconstruct the resulting associations between the musical content in order to investigate their underlying meanings. Network analysis detects 50 clusters of tightly connected videos characterised by a strong internal homogeneity across different axes of similarity. We discuss these findings with reference to the literature on music genres and classification, arguing that the emerging clusters can be considered as ‘crowd-generated music categories'. That is, sets of musical content that derive from the repeated, crowd-based actions of sequential viewing by users on YouTube in combination with the platform's algorithm. Interestingly, 7 out of 50 clusters are characterised by what may be seen as a ‘situational' culture of music reception by digital audiences. Such culture is not so much founded on music genres as traditionally conceived, but rather on the purposes of reception which are rooted in the context where this takes place.

Suggested Citation

  • Massimo Airoldi & Davide Beraldo & Alessandro Gandini, 2016. "Follow the algorithm : An exploratory investigation of music on YouTube," Post-Print hal-02312191, HAL.
    • Handle: RePEc:hal:journl:hal-02312191
    DOI: 10.1016/j.poetic.2016.05.001
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    Citations

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    Cited by:

    1. Ariadna Matamoros-Fernández & Joanne E. Gray & Louisa Bartolo & Jean Burgess & Nicolas Suzor, 2021. "What’s “Up Next”? Investigating Algorithmic Recommendations on YouTube Across Issues and Over Time," Media and Communication, Cogitatio Press, vol. 9(4), pages 234-249.
    2. Dana Adriana Lupșa-Tătaru & Radu Lixăndroiu, 2022. "YouTube Channels, Subscribers, Uploads and Views: A Multidimensional Analysis of the First 1700 Channels from July 2022," Sustainability, MDPI, vol. 14(20), pages 1-13, October.
    3. Steffen Lepa & Jochen Steffens & Martin Herzog & Hauke Egermann, 2020. "Popular Music as Entertainment Communication: How Perceived Semantic Expression Explains Liking of Previously Unknown Music," Media and Communication, Cogitatio Press, vol. 8(3), pages 191-204.

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