Hit Song Prediction Based on Early Adopter Data and Audio Features
Sound
2020-10-20 v1 Machine Learning
Multimedia
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.
Keywords
Cite
@article{arxiv.2010.09489,
title = {Hit Song Prediction Based on Early Adopter Data and Audio Features},
author = {Dorien Herremans and Tom Bergmans},
journal= {arXiv preprint arXiv:2010.09489},
year = {2020}
}