Personality Traits and Music Genres: What Do People Prefer to Listen To?

被引:35
|
作者
Ferwerda, Bruce [1 ]
Tkalcic, Marko [2 ]
Schedl, Markus [1 ]
机构
[1] Johannes Kepler Univ Linz, Dept Computat Percept, Altenberger Str 69, A-4040 Linz, Austria
[2] Free Univ Bozen Bolzano, Fac Comp Sci, Piazza Domenicani 3, I-39100 Bozen Bolzano, Italy
基金
奥地利科学基金会;
关键词
Music; Personality; Recommender Systems; User Modeling;
D O I
10.1145/3079628.3079693
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Personality-based personalized systems are increasingly gaining interest as personality traits has been shown to be a stable construct within humans. In order to provide a personality-based experience to the user, users' behavior, preferences, and needs in relation to their personality need to be investigated. Although for a technological mediated environment the search for these relationships is often new territory, there are findings from personality research of the real world that can be used in personalized systems. However, for these findings to be implementable, we need to investigate whether they hold in a technologically mediated environment. In this study we assess prior work on personality-based music genre preferences from traditional personality research. We analyzed a dataset consisting of music listening histories and personality scores of 1415 Last.fm users. Our results show agreements with prior work, but also important differences that can help to inform personalized systems.
引用
收藏
页码:285 / 288
页数:4
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