K. Robinson, D. Brown, Markus Schedl,
"User Insights on Diversity in Music Recommendation Lists"
: Proceedings of the 21th International Society for Music Information Retrieval Conference (ISMIR 2020), 10-2020
Original Titel:
User Insights on Diversity in Music Recommendation Lists
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the 21th International Society for Music Information Retrieval Conference (ISMIR 2020)
Original Kurzfassung:
While many researchers have proposed various ways
of quantifying recommendation list diversity, these approaches have had little input from users on their own perceptions and preferences in seeking diversity. Through an
exploratory user study, we provide a better understanding
of how users view the concept of diversity in music recommendations, and how they might optimise levels of intralist diversity themselves. In our study, 17 participants interacted with and rated the suggestions from two different
recommendation systems. One provided static top-7 collaborative filtering recommendations, and the other provided an interactive slider to re-rank these recommendations based on a continuous diversity scale. We also asked
participants a series of free-form questions on music discovery and diversity in semi-structured interviews. Userpreferred levels of diversity varied widely both within and
between subjects. Although most users agreed that diversity is beneficial in music discovery, they also noted a risk
of dissatisfaction from too much diversity. A key finding is
that preference for diversification was often linked to user
mood. Participants also expressed a clear distinction between diversity within existing preferences, and outside of
existing preferences. These ideas of inner and outer diversity are not well defined within the bounds of current
diversity metrics, and we discuss their implications.