Music success (feat. RDF): A study on music features’ contribution to music success in Spotify through random decision forests.

• Main Authors: Cu, Irizze Gail L., Espanola, Jibril Denn S., Lim, Kirsten Nicholle B., Mercado, Juan Lorenzo J.
• Format: text
• Language: English
• Published: Animo Repository 2022
• Subjects: Music trade; Other Business
• Online Access: https://animorepository.dlsu.edu.ph/etdb_dsi/91; https://animorepository.dlsu.edu.ph/context/etdb_dsi/article/1057/viewcontent/Music_Success__feat._RDF___A_Study_on_Music_Features__Contributio_Redacted2.pdf
• Institution: De La Salle University

The growing use of predictive analysis can be seen in volatile industries such as the music industry. Our study contributed to determining which song features are able to assist a song in making it to the top charts with the use of a feature ranking model to establish which specific features are dee...