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.
Models citing this paper 0
No model linking this paper
Cite arxiv.org/abs/2010.09489 in a model README.md to link it from this page.
Datasets citing this paper 0
No dataset linking this paper
Cite arxiv.org/abs/2010.09489 in a dataset README.md to link it from this page.
Spaces citing this paper 0
No Space linking this paper
Cite arxiv.org/abs/2010.09489 in a Space README.md to link it from this page.
Collections including this paper 0
No Collection including this paper
Add this paper to a
collection
to link it from this page.