Predicting Sentiments in Spotify Comments: A Comparative Analysis of Machine Learning Models

Authors

DOI:

https://doi.org/10.51359/2965-4661.2024.265070

Keywords:

Natural Language Processing, Spotify, Machine Learning, Logistic Regression, Random Forest, sentiment analysis

Abstract

Using data from user sentences on Spotify, this work explores through Natural Language Processing positive and negative sentiments in each comment. We compare different statistical modeling and Machine Learning techniques, identifying the ones with the greatest accuracy in predicting sentiments. As a result, the assessment supports most of the sentences presented with negative connotations. As for modeling, the Logistic Regression and Random Forest models resulted in better accuracy.

References

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Published

2024-12-20

Issue

Vol. 2 No. 1 (2024)

Section

Research Articles

License

Copyright (c) 2024 Filipe Augusto Felix de Queiroz, Igor Barbosa Negreiros, Giovana de Souza, Débora Cordeiro de Sousa, Sílvio Fernando Alves Xavier Júnior

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