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Communication Dans Un Congrès Année : 2018

How Automated Recommendations Affect the Playlist Creation Behavior of Users

Résumé

Modern music platforms like Spotify support users to create new playlists through interactive tools. Given an empty or initial playlist, these tools often recommend additional songs, which could be included in the playlist based, e.g., on the title of the playlist or the set of tracks that are already in the playlist. In this work, we analyze in which ways the recommendations of such playlist construction support tools influence the behavior of users and the characteristics of the resulting playlists. We report the results of a between-subjects user study involving 123 subjects. Our analysis shows that users provided with recommendation support were more engaged and explored more alternatives than the control group. Presumably influenced by the recommender, they also picked significantly less popular items, which leads to a higher potential for discovery. The effort required to browse the additional alternatives, however, increased the users' perceived difficulty of the process.
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Dates et versions

hal-02476919 , version 1 (13-02-2020)

Identifiants

  • HAL Id : hal-02476919 , version 1

Citer

Iman Kamehkhosh, Dietmar Jannach, Geoffray Bonnin. How Automated Recommendations Affect the Playlist Creation Behavior of Users. ACM IUI 2018 - Workshops, 2018, Tokyo, Japan. ⟨hal-02476919⟩
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