Multiclass Emotion Detection of Bangla Verse Text using NLP and Predictive Machine Learning Models

This study makes three main contributions. First, it introduces a new annotated dataset containing more than 18,000 Bangla poetic and song-lyric samples, categorized into seven emotion classes: Patriotism, Joy, Love, Sadness, Anger, Fear, and Surprise. The inclusion of Patriotism captures an important emotion-specific dimension of Bangla literary and cultural expression. Second, we develop a systematic modeling framework incorporating classical machine learning models, a hybrid stacking ensemble, and fine-tuned Bangla-BERT, enabling a comprehensive and consistent comparison of diverse modeling approaches. Third, we investigate the effects of class imbalance and provide detailed class-wise performance analysis, offering deeper insights into model strengths, limitations, and challenges in Bangla emotion classification.