Measuring spontaneous devaluations in user preferences

Authors:
Komal Kapoor;Nisheeth Srivastava;Jaideep Srivastava;Paul Schrater
Affiliations:
University of Minnesota, Minneapolis, Minnesota, USA;University of Minnesota, Minneapolis, Minnesota, USA;University of Minnesota, Minneapolis, Minnesota, USA;University of Minnesota, Minneapolis, Minnesota, USA
Venue:
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Year:
2013

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Abstract

Spontaneous devaluation in preferences is ubiquitous, where yesterday's hit is today's affliction. Despite technological advances facilitating access to a wide range of media commodities, finding engaging content is a major enterprise with few principled solutions. Systems tracking spontaneous devaluation in user preferences can allow prediction of the onset of boredom in users potentially catering to their changed needs. In this work, we study the music listening histories of Last.fm users focusing on the changes in their preferences based on their choices for different artists at different points in time. A hazard function, commonly used in statistics for survival analysis, is used to capture the rate at which a user returns to an artist as a function of exposure to the artist. The analysis provides the first evidence of spontaneous devaluation in preferences of music listeners. Better understanding of the temporal dynamics of this phenomenon can inform solutions to the similarity-diversity dilemma of recommender systems.