Forecasting Song Success: Predicting Billboard Hot 100 Performance And Identifying Key Contributing Factors

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Keywords	Hit song science, Machine learning, Chart longevity, Features, Peak position, Billboard Hot 100
Thesis Advisor	Ponte, Gillian, Kusterer, David Jakob
Persistent URL	hdl.handle.net/2105/71946
Series	Business Analytics & Management
Organisation	Rotterdam School of Management
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Broerse, Kim. (2024, July 2). Forecasting Song Success: Predicting Billboard Hot 100 Performance And Identifying Key Contributing Factors. Business Analytics & Management. Retrieved from http://hdl.handle.net/2105/71946

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