Consumption and Design of Music Albums and Personalized Playlists

Khaled Boughanmi, Columbia University

Khaled Boughanmi will present research, conducted with Asim Ansari and Rajeev Kohli, that uses a nonparametric Bayesian model combining online data of different modalities (e.g., metadata, acoustic and textual data) to explore the dynamics of musical success of albums over the last half century. One model component uses a supervised hierarchical Dirichlet process to summarize the perceptual information in crowd-sourced textual tags. Another time-varying component uses dynamic penalized splines to capture how different acoustical features of music have shaped album success. By analyzing how various subjective and objective acoustic measures have waxed and waned in importance over the years, Boughanmi, Ansari and Kohli uncover a number of themes that categorize albums in terms of sub-genres, consumption contexts, emotions, nostalgia and other aspects of the musical experience. Their model estimates can be used to compile new albums and playlists to appeal to listeners with different preferences and requirements.

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