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...
Saved in:
| Main Authors: | Filipe Augusto Felix de Queiroz, Igor Barbosa Negreiros, Giovana de Souza, Débora Cordeiro de Sousa, Sílvio Fernando Alves Xavier Júnior |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universidade Federal de Pernambuco (UFPE)
2024-12-01
|
| Series: | Socioeconomic Analytics |
| Subjects: | |
| Online Access: | https://periodicos.ufpe.br/revistas/index.php/SECAN/article/view/265070 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
How to make a hit: factors associated with music consumption on Spotify
by: Ana Flávia Machado, et al.
Published: (2025-05-01) -
How to make a hit: factors associated with music consumption on Spotify
by: Ana Flávia Machado, et al.
Published: (2025-05-01) -
THE FULFILLMENT OF ECONOMIC RIGHTS IN SPOTIFY
by: Cloudio Ardelle Hitipeuw, et al.
Published: (2025-05-01) -
ENHANCING ENGLISH PRONUNCIATION STRESS PATTERNS THROUGH LYRIC-BASED SONG ON SPOTIFY
by: Marrieta Moddies Swara, et al.
Published: (2025-05-01) -
An exploration of user engagement and communication strategies on Spotify: a uses and gratifications perspective
by: Elsir Ali Saad Mohamed, et al.
Published: (2025-05-01)