Reflektor: An Exploration of Collaborative Music Playlist Creation for Social Context

Jared S. Bauer, Aubury L. Jellenek, J. Kientz
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引用次数: 5

Abstract

Music is intrinsically linked to our social lives. As more music becomes available through streaming services, deciding what music is appropriate for social events becomes increasingly challenging and nuanced. While prior work has considered the social role of music and the creation of music playlists for user contexts, how individuals utilize music to create social contexts is an area that has largely gone unexplored. To investigate this topic, we created and evaluated a prototype music recommender system called Reflektor. Reflektor interactively visualizes users' chat conversations to generate music playlists. Our analysis of user conversations with Reflektor uncovered distinct strategies participants use to create the ambiance and conduct for social contexts. Our findings help to illuminate mismatches in the way metadata and recommendation systems align with user strategies to create social context. We elaborate on these strategies and discuss design implications for future collaborative music recommender systems.
Reflektor:社会背景下合作音乐播放列表创作的探索
音乐与我们的社会生活有着内在的联系。随着越来越多的音乐可以通过流媒体服务获得,决定什么音乐适合社交活动变得越来越具有挑战性和微妙。虽然之前的工作已经考虑了音乐的社会角色和为用户情境创建音乐播放列表,但个人如何利用音乐来创建社会情境是一个很大程度上未被探索的领域。为了研究这个主题,我们创建并评估了一个名为Reflektor的原型音乐推荐系统。Reflektor交互式可视化用户的聊天对话,以生成音乐播放列表。我们通过对Reflektor用户对话的分析发现,参与者使用不同的策略来为社交环境创造氛围和行为。我们的研究结果有助于阐明元数据和推荐系统与用户策略一致以创建社交环境的方式的不匹配。我们详细阐述了这些策略,并讨论了未来协同音乐推荐系统的设计含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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