# Dance Hit Song Prediction

arXiv: https://arxiv.org/abs/1905.08076 · HTML: https://mlsanity.com/paper/1905.08076/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 May 2019.

## Built on by (most cited first, 3 of 3)

- [An Analysis of Classification Approaches for Hit Song Prediction using Engineered Metadata Features with Lyrics and Audio Features](https://mlsanity.com/paper/2301.13507/) (2023)
- [Lyrics Matter: Exploiting the Power of Learnt Representations for Music Popularity Prediction](https://mlsanity.com/paper/2512.05508/) (2025)
- [APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music](https://mlsanity.com/paper/2605.03395/) (2026)

## Abstract (arXiv)

Record companies invest billions of dollars in new talent around the globe each year. Gaining insight into what actually makes a hit song would provide tremendous benefits for the music industry. In this research we tackle this question by focussing on the dance hit song classification problem. A database of dance hit songs from 1985 until 2013 is built, including basic musical features, as well as more advanced features that capture a temporal aspect. A number of different classifiers are used to build and test dance hit prediction models. The resulting best model has a good performance when predicting whether a song is a "top 10" dance hit versus a lower listed position.