Abstract
Music streaming services increasingly incorporate different ways for users to browse for
music. Next to the commonly used “genre” taxonomy, nowadays additional taxonomies,
such as mood and activities, are often used. As additional taxonomies have shown to be
able to distract the user in their search, we looked at how to predict taxonomy preferences
in order to counteract this. Additionally, we looked at how the number of categories presented
within a taxonomy influences the user experience. We conducted an online user
study where participants interacted with an application called “Tune-A-Find”.We measured
taxonomy choice (i.e., mood, activity, or genre), individual differences (e.g., personality
traits and music expertise factors), and different user experience factors (i.e., choice difficulty
and satisfaction, perceived system usefulness and quality) when presenting either
6- or 24-categories within the picked taxonomy. Among 297 participants, we found that personality
traits are related to music taxonomy preferences. Furthermore, our findings show
that the number of categories within a taxonomy influences the user experience in different
ways and is moderated by music expertise. Our findings can support personalized user
interfaces in music streaming services. By knowing the user’s personality and expertise, the
user interface can adapt to the user’s preferred way of music browsing and thereby mitigate
the problems that music listeners are facing while finding their way through the abundance
of music choices online nowadays.
Original language | English |
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Number of pages | 34 |
Journal | Multimedia Tools and Applications |
DOIs | |
Publication status | Published - 2019 |
Fields of science
- 202002 Audiovisual media
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102015 Information systems
JKU Focus areas
- Digital Transformation