Abstract
Past studies have shown that personality has a significant association with user behaviour and preferences, not least towards music. This makes personality information a promising aspect for user modelling in personalised recommender systems and similar domains. In contrast to existing studies, which investigate personality correlates of music preferences via genres or styles, we study such correlates by modelling music preferences at a finer-grained content level, using audio features of the music users listen to. Leveraging listening and personality information of more than 1,300 Last.fm users, we identify several significant medium and weak correlations between music audio features and personality traits, the latter defined by the five-factor model. Our results provide useful insights into the relationship between personality and music preference, which can be valuable for music recommender systems in terms of more personalised recommendations.
Citation
Alessandro B.
Melchiorre,
Markus
Schedl
Personality Correlates of Music Audio Preferences for Modelling Music Listeners
Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization (UMAP),
313–-317, doi:10.1145/3340631.3394874, 2020.
BibTeX
@article{Melchiorre2020PersonalityCorrelates,
title = {Personality Correlates of Music Audio Preferences for Modelling Music Listeners},
author = {Melchiorre, Alessandro B. and Schedl, Markus},
booktitle = {Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization (UMAP)},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
doi = {10.1145/3340631.3394874},
url = {https://doi.org/10.1145/3340631.3394874},
pages = {313–-317},
location = {Virtual Event, Genoa, Italy},
year = {2020}
}