Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-8689
Main Title: Modeling Music-Selection Behavior in Everyday Life: A Multilevel Statistical Learning Approach and Mediation Analysis of Experience Sampling Data
Author(s): Greb, Fabian
Steffens, Jochen
Schlotz, Wolff
Type: Article
Language Code: en
Abstract: Music listening has become a highly individualized activity with smartphones and music streaming services providing listeners with absolute freedom to listen to any kind of music in any situation. Until now, little has been written about the processes underlying the selection of music in daily life. The present study aimed to disentangle some of the complex processes among the listener, situation, and functions of music listening involved in music selection. Utilizing the experience sampling method, data were collected from 119 participants using a smartphone application. For 10 consecutive days, participants received 14 prompts using stratified-random sampling throughout the day and reported on their music-listening behavior. Statistical learning procedures on multilevel regression models and multilevel structural equation modeling were used to determine the most important predictors and analyze mediation processes between person, situation, functions of listening, and music selection. Results revealed that the features of music selected in daily life were predominantly determined by situational characteristics, whereas consistent individual differences were of minor importance. Functions of music listening were found to act as a mediator between characteristics of the situation and music-selection behavior. We further observed several significant random effects, which indicated that individuals differed in how situational variables affected their music selection behavior. Our findings suggest a need to shift the focus of music-listening research from individual differences to situational influences, including potential person-situation interactions.
URI: https://depositonce.tu-berlin.de/handle/11303/9643
http://dx.doi.org/10.14279/depositonce-8689
Issue Date: 19-Mar-2019
Date Available: 19-Jul-2019
DDC Class: 150 Psychologie
780 Musik
Subject(s): music-listening behavior
music-selection behavior
functions of music listening
machine learning
experience sampling method
user behavior analysis
License: https://creativecommons.org/licenses/by/4.0/
Journal Title: Frontiers in Psychology
Publisher: Frontiers
Publisher Place: Lausanne
Volume: 10
Article Number: 390
Publisher DOI: 10.3389/fpsyg.2019.00390
EISSN: 1664-1078
Appears in Collections:FG Audiokommunikation » Publications

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