# Hit Song Prediction Based on Early Adopter Data and Audio Features

arXiv: https://arxiv.org/abs/2010.09489 · HTML: https://mlsanity.com/paper/2010.09489/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Oct 2020.

## Built on by (most cited first, 1 of 1)

- [APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music](https://mlsanity.com/paper/2605.03395/) (2026)

## Abstract (arXiv)

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.