Dance hit song prediction

Dorien Herremans, David Martens and Kenneth Sörensen

Working Papers from University of Antwerp, Faculty of Business and Economics

Abstract: 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 focusing 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.

Keywords: Data mining; Classification; Prediction; Music Information Retrieval (MIR) (search for similar items in EconPapers)
JEL-codes: C6 C8 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2014-02
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:ant:wpaper:2014003

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