Abstract
Hit Song Science (HSS) is an emerging topic that aims to unveil the success dynamics within the music industry. Considering the growth of the area, we provide a comprehensive study with a complete review of the main topics of this interdisciplinary field from a computer science perspective. We also define a generic workflow for HSS, introduce taxonomies for success measures and musical features, and categorize the main current learning algorithms. Overall, this survey may serve as a starting point for future research on HSS, as it emerges as a promising field that benefits both the academy and the music industry.
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