Personalised But Impersonal: Listeners' Experiences of Algorithmic Curation on Music Streaming Services
Sophie O. Freeman, Martin R. Gibbs, Bjorn Nansen
摘要
The consumption of music is increasingly reliant on the personalisation, recommendation, and automated curation features of music streaming services. Using algorithm experience (AX) as a lens, we investigated the user experience of the algorithmic recommendation and automated curation features of several popular music streaming services. We conducted interviews and participant-observation with 15 daily users of music streaming services, followed by a design workshop. We found that despite the utility of increasingly algorithmic personalisation, listeners experienced these algorithmic and recommendation features as impersonal in determining their background listening, music discovery, and playlist curation. While listener desire for more control over recommendation settings is not new, we offer a number of novel insights about music listening to nuance this understanding, particularly through the notion of vibe.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
引用它的顶会 Paper1
问问它们各自怎么用它相关 Paper
- Algorithmic Effects on the Diversity of Consumption on SpotifyAshton Anderson, Lucas Maystre, Ian Anderson, Rishabh Mehrotra 等WWW 2020 · 被引用 211 次
- Social Music Curation That Works: Insights from Successful Collaborative PlaylistsSo Yeon Park, Blair KaneshiroCSCW 2021 · 被引用 20 次
- Giving Voice to Silent Data: Designing with Personal Music Listening HistoryJordan Wirfs-Brock, Sarah Mennicken, Jennifer ThomCHI 2020 · 被引用 24 次
- Investigating the Potential of Group Recommendation Systems As a Medium of Social Interactions: A Case of Spotify Blend Experiences between Two UsersDaehyun Kwak, Soobin Park, Inha Cha, Hankyung Kim 等CHI 2024 · 被引用 7 次
- Beyond Explicit and Implicit: How Users Provide Feedback to Shape Personalized Recommendation ContentWenqi Li, Jui-Ching Kuo, Manyu Sheng, Pengyi Zhang 等CHI 2025 · 被引用 14 次
