User Modeling

Serving the diverse needs of millions of users requires the development of technology to not only understand user tastes and interests, but also consider contextual preferences of the users to serve them relevant, timely and inspirational recommendations. The user modeling research at Spotify entails translating users’ in-app activities into human traits, interaction models, emotional understanding modules, and situational contexts, thereby uncovering our users’ individuality. To do this, we use a multidisciplinary scientific approach at the intersection of music psychology, behavioral analysis, and machine learning. This enables us to build datasets and user interaction models to create engaging and personalized experiences for our users, in a data-driven fashion based on users’ interactions and feedback signals.

Latest User Modeling Publications

November 2022 | NeurIPS

Temporally-Consistent Survival Analysis

Lucas Maystre, Daniel Russo

August 2022 | UAI

Multistate analysis with infinite mixtures of Markov chains

Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara

June 2022 | ICWSM

Time after Time: Longitudinal Trends in Nostalgic Listening

Clara Hanson, Jesse Anderton, Samuel F. Way, Ian Anderson, Scott Wolf, Alice Wang

Other Research Areas