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
-
Copyright Protection for Songs Uploaded to the Spotify Digital Music Application Without Permission
by: Maichel Lesnussa, et al.
Published: (2024-11-01) -
Reddit comment analysis: sentiment prediction and topic modeling using VADER and BERTopic
by: Denilson de Oliveira Silva, et al.
Published: (2024-12-01) -
The Portuguese consumer sentiment index toward marketing-mix in crisis context
by: Paula Odete Fernandes, et al.
Published: (2013-01-01) -
Multi-Class Sentiment Analysis on Twitter: Classification Performance and Challenges
by: Mondher Bouazizi, et al.
Published: (2019-09-01) -
Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning
by: Ashagrew Liyih, et al.
Published: (2024-06-01)