arXiv · 2010.09489
Hit Song Prediction Based on Early Adopter Data and Audio Features
Abstract
Billions of USD are invested in new artists and songs by the music industry every year. This research provides a new strategy for assessing the hit potential of songs, which can help record companies support their investment decisions. A number of models were developed that use both audio data, and a novel feature based on social media listening behaviour. The results show that models based on early adopter behaviour perform well when predicting top 20 dance hits.
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Dorien Herremans, Tom Bergmans. 2020-10-16. Hit Song Prediction Based on Early Adopter Data and Audio Features. https://arxiv.org/abs/2010.09489
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