https://github.com/alain-godo/spotify-popularity

A simple analysis and modeling for prediction of the popularity of songs on Spotify
https://github.com/alain-godo/spotify-popularity

linear-regression machine-learning numpy pandas random-forest sckiit-learn spotify tree-decision

Last synced: about 2 months ago
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A simple analysis and modeling for prediction of the popularity of songs on Spotify

• Host: GitHub
• URL: https://github.com/alain-godo/spotify-popularity
• Owner: Alain-Godo
• License: mit
• Created: 2023-04-18T20:03:21.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2023-04-18T21:56:33.000Z (about 3 years ago)
• Last Synced: 2026-03-29T20:08:21.692Z (3 months ago)
• Topics: linear-regression, machine-learning, numpy, pandas, random-forest, sckiit-learn, spotify, tree-decision
• Language: Jupyter Notebook
• Homepage:
• Size: 248 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Spotify popularity

This is a simple attempt to analyze the popularity reached by global songs (1922-2021) using features obtained from the Spotify API. To predict the popularity is selected the best-performed model from the following techniques: Linear Regression, Tree Decision, and Random Forest. 

Two versions of the Random Forest model are made, taking or not into consideration the artist's name as a feature, showing the influence of marketing and social media on the results. 

### Acknowledgements:

https://www.kaggle.com/sumaya23abdul