Leveraging Multilingual Transformer for Multiclass Sentiment Analysis in Code-Mixed Data of Low-Resource Languages

The widespread use of online social media has enabled users to express their thoughts, feelings, opinions, and sentiments in their preferred languages. These diverse perspectives offer valuable insights for data-driven decision-making. While extensive sentiment analysis approaches have been develope...

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Detalles Bibliográficos

Autores principales:	Muhammad Kashif Nazir, Cm Nadeem Faisal, Muhammad Asif Habib, Haseeb Ahmad
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	IEEE 2025-01-01
Colección:	IEEE Access
Materias:	Code-mixed dataset classification low resource languages mBERT sentiment analysis transformer
Acceso en línea:	https://ieeexplore.ieee.org/document/10835765/
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