Clara Hanson, Jesse Anderton, Samuel F. Way, Ian Anderson, Scott Wolf, Alice Wang
“Just The Way You Are”: Linking Music Listening on Spotify and Personality
Advances in digital technology have put music libraries at people’s fingertips, giving them immediate access to more music than ever before. Here we overcome limitations of prior research by leveraging ecologically valid streaming data: 17.6 million songs and over 662,000 hr of music listened to by 5,808 Spotify users spanning a 3-month period. Building on interactionist theories, we investigated the link between personality traits and music listening behavior, described by an extensive set of 211 mood, genre, demographic, and behavioral metrics. Findings from machine learning showed that the Big Five personality traits are predicted by musical preferences and habitual listening behaviors with moderate to high accuracy. Importantly, our work contrasts a recent self-report-based meta-analysis, which suggested that personality traits play only a small role in musical preferences; rather, we show with big data and advanced machine learning methods that personality is indeed important and warrants continued rigorous investigation.
Lillio Mok, Samuel F. Way, Lucas Maystre, Ashton Anderson
Mostra: A Flexible Balancing Framework to Trade-off User, Artist and Platform Objectives for Music Sequencing
Emanuele Bugliarello, Rishabh Mehrotra, James Kirk, Mounia Lalmas