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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Bibliografiska uppgifter

Huvudupphov:	Muhammad Kashif Nazir, Cm Nadeem Faisal, Muhammad Asif Habib, Haseeb Ahmad
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	IEEE 2025-01-01
Serie:	IEEE Access
Ämnen:	Code-mixed dataset classification low resource languages mBERT sentiment analysis transformer
Länkar:	https://ieeexplore.ieee.org/document/10835765/
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