Papers
arxiv:2010.09489
Hit Song Prediction Based on Early Adopter Data and Audio Features
Published on Oct 16, 2020
Abstract
A novel model incorporating social media listening behavior effectively predicts the hit potential of dance songs by analyzing early adopter behavior.
AI-generated summary
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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