Enhancing Sentiment and Emotion Classification with LSTM-Based Semi-Supervised Learning

Enhancing Sentiment and Emotion Classification with LSTM-Based Semi-Supervised Learning

The evolution of sentiment analysis has increasingly relied on semi-supervised learning (SSL) models, particularly due to their efficiency in utilizing large amounts of unlabeled data. This study employed four Indonesian datasets—Ridife (sentiment classification), Emotion Indonlu (emotion classifica...

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Bibliographic Details
Main Authors: Rochmat Husaini, Nur Heri Cahyana, Wisnalmawati Wisnalmawati, Tri Mardiana, Yuli Fauziah
Format: Article
Language:English
Published: Institut Teknologi Dirgantara Adisutjipto 2025-06-01
Series:Compiler
Subjects:
semi-supervised learning
lstm
sentiment analysis
Online Access:https://ejournals.itda.ac.id/index.php/compiler/article/view/2965
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