Predicting Song Popularity Through Machine Learning and Sentiment Analysis on Social Networks

Author:

Rompolas GerasimosORCID,Smpoukis AthanasiosORCID,Kafeza EleannaORCID,Makris ChristosORCID

Publisher

Springer Nature Switzerland

Reference25 articles.

1. IFPI Global Music Report (2023). https://www.ifpi.org/ifpi-global-music-report-global-recorded-music-revenues-grew-9-in-2022/. Accessed 10 Feb 2024

2. Aum, J., Kim, J., Park, E.: Can we predict the billboard music chart winner? Machine learning prediction based on twitter artist-fan interactions. Behav. Inf. Technol. 42, 1–14 (2022)

3. Bird, S., Klein, E., Loper, E.: Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. O’Reilly Media Inc, Sebastopol (2009)

4. Breiman, L.: Random forests. Mach. Learning 45(1), 5–32 (2001)

5. Breiman, L.: Classification and Regression Trees. Routledge, Boca Raton (2017)

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