Bruce Ferwerda, E. Yang, Markus Schedl, Marko Tkalcic,
"Personality Traits Predict Music Taxonomy Preferences."
: Proceedings of the ACM Conference on Human Factors in Computing Systems Extended Abstracts (CHI), 2015
Original Titel:
Personality Traits Predict Music Taxonomy Preferences.
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the ACM Conference on Human Factors in Computing Systems Extended Abstracts (CHI)
Original Kurzfassung:
Music streaming services increasingly incorporate
additional music taxonomies (i.e., mood, activity, and
genre) to provide users different ways to browse through
music collections. However, these additional taxonomies
can distract the user from reaching their music goal, and
influence choice satisfaction. We conducted an online user
study with an application called \Tune-A-Find," where we
measured participants' music taxonomy choice (mood,
activity, and genre). Among 297 participants, we found
that the chosen taxonomy is related to personality traits.
We found that openness to experience increased the
choice for browsing music by mood, while
conscientiousness increased the choice for browsing music
by activity. In addition, those high in neuroticism were
most likely to browse for music by activity or genre. Our
findings can support music streaming services to further
personalize user interfaces. By knowing the user's
personality, the user interface can adapt to the user's
preferred way of music browsing.