Classifying Spotify Song Trends with SoundSoar: Machine Learning Insights for Content Creation and Marketing

SoundSoar applies machine learning to predict Spotify song popularity trends—“up,” “down,” or “stable”—using engineered audio features and historical data. Among eight tested classifiers, the MLP achieved 97.0% accuracy, while ensemble models like Random Forest consistently performed well (90.0%–91.0%). By leveraging a tailored dataset and diverse models, this approach improves upon broader trend prediction methods. Despite challenges from Spotify API changes in late 2024, our findings validate machine learning’s role in music trend forecasting and set the stage for future enhancements, such as custom sound analysis and cross-platform models.

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Publication Details

Journal
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Published
2025-05-14
DOI
https://doi.org/10.32473/flairs.38.1.139012
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00
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article

Classifying Spotify Song Trends with SoundSoar: Machine Learning Insights for Content Creation and Marketing

Valentina Grasso, Andreas Marpaung
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Music and Audio Processing
article

Classifying Spotify Song Trends with SoundSoar: Machine Learning Insights for Content Creation and Marketing

Valentina Grasso, Andreas Marpaung
article en

Abstract

SoundSoar applies machine learning to predict Spotify song popularity trends—“up,” “down,” or “stable”—using engineered audio features and historical data. Among eight tested classifiers, the MLP achieved 97.0% accuracy, while ensemble models like Random Forest consistently performed well (90.0%–91.0%). By leveraging a tailored dataset and diverse models, this approach improves upon broader trend prediction methods. Despite challenges from Spotify API changes in late 2024, our findings validate machine learning’s role in music trend forecasting and set the stage for future enhancements, such as custom sound analysis and cross-platform models.

Proceedings of the ... International Florida Artificial Intelligence Research Society ConferenceVol. 38
Full Sail University (US)
Openalex Percentile: Top 74%
Music and Audio Processing
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