Predicting Sentiments in Spotify Comments: A Comparative Analysis of Machine Learning Models
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.
Authors
- Sílvio Fernando Alves Xavier Júnior (ORCID: https://orcid.org/0000-0002-4832-0711)
- G. D. G. De Souza
- Filipe Augusto Felix de Queiroz
- Igor Barbosa Negreiros
- Débora Cordeiro de Sousa
Institutions
- Universidade Estadual da Paraíba (BR)
Publication Details
- Journal
- Socioeconomic Analytics
- Published
- 2024-12-20
- DOI
- https://doi.org/10.51359/2965-4661.2024.265070
- Citations
- 1
- Primary Topic
- Sentiment Analysis and Opinion Mining
- Type
- article
- Field-Weighted Citation Impact
- 0.35