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The skipping behavior of users of music streaming services and its relation to musical structure

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  • Nicola Montecchio
  • Pierre Roy
  • François Pachet

Abstract

The behavior of users of music streaming services is investigated from the point of view of the temporal dimension of individual songs. Specifically, the main object of the analysis is the point in time within a song at which users stop listening and start streaming another song (“skip”). The main contribution of this study is the ascertainment of a correlation between the distribution in time of skipping events and the musical structure of songs. It is also shown that such distribution is not only specific to the individual songs, but also independent of the cohort of users and date of observation. Finally, user behavioral data is used to train a predictor of the musical structure of a song solely from its acoustic content; it is shown that the use of such data, available in large quantities to music streaming services, yields significant improvements in accuracy over the customary fashion of training this class of algorithms, in which only smaller amounts of hand-labeled data are available.

Suggested Citation

  • Nicola Montecchio & Pierre Roy & François Pachet, 2020. "The skipping behavior of users of music streaming services and its relation to musical structure," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-16, September.
    • Handle: RePEc:plo:pone00:0239418
    DOI: 10.1371/journal.pone.0239418
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    References listed on IDEAS

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    1. HERREMANS, Dorien & MARTENS, David & SÖRENSEN, Kenneth, 2014. "Dance hit song prediction," Working Papers 2014003, University of Antwerp, Faculty of Business and Economics.
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    Cited by:

    1. Emaad Manzoor & Nikhil Malik, 2023. "Designing Effective Music Excerpts," Papers 2309.14475, arXiv.org.

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