Dance Hit Song Prediction
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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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 May 2019.
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Citing papers per year: 2023: 1; 2024: 0; 2025: 1; 2026: 1.
3 papers.
- 2023An Analysis of Classification Approaches for Hit Song Prediction using Engineered Metadata Features with Lyrics and Audio Featurescited by 2
- 2025Lyrics Matter: Exploiting the Power of Learnt Representations for Music Popularity Predictioncited by 1
- 2026APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Musiccited by 0
- 2026APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music5 May 2026
- 2025Lyrics Matter: Exploiting the Power of Learnt Representations for Music Popularity Prediction5 Dec 2025
- 2023An Analysis of Classification Approaches for Hit Song Prediction using Engineered Metadata Features with Lyrics and Audio Features31 Jan 2023