From Exploration to Exploitation: Understanding the Evolution of Music Careers through a Data-driven Approach

Abstract

We propose a data-driven methodology to analyze how music artists spread their interest (explore) and focus their attention (exploit) on distinct music topics (genres) while having peaks of success (hot streaks). Music topics are identified through community detection over a complex network modeling of artists, songs and their genres. Then, we analyze exploration and exploitation by measuring the entropy and quantifying it in three periods: before, during and after hot streaks. Results show artists explore topics before hitting their first hot streak and during their most successful period. After, they tend to reduce the range of topics by going deeper in a handful only. Such findings are relevant for identifying and nurturing creative talent in the music industry.