GeeSanBhava: Sentiment Tagged Sinhala Music Video Comment Data Set
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Abstract (arXiv)
This study introduce GeeSanBhava, a high-quality data set of Sinhala song comments extracted from YouTube manually tagged using Russells Valence-Arousal model by three independent human annotators. The human annotators achieve a substantial inter-annotator agreement (Fleiss kappa = 84.96%). The analysis revealed distinct emotional profiles for different songs, highlighting the importance of comment based emotion mapping. The study also addressed the challenges of comparing comment-based and song-based emotions, mitigating biases inherent in user-generated content. A number of Machine learning and deep learning models were pre-trained on a related large data set of Sinhala News comments in order to report the zero-shot result of our Sinhala YouTube comment data set. An optimized Multi-Layer Perceptron model, after extensive hyperparameter tuning, achieved a ROC-AUC score of 0.887. The model is a three-layer MLP with a configuration of 256, 128, and 64 neurons. This research contributes a valuable annotated dataset and provides insights for future work in Sinhala Natural Language Processing and music emotion recognition.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 9 of its 24 references that are in the map. First posted on arXiv 22 Nov 2025.
Builds on
9 of 24 references.
References · 9
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
- 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,474
- 2016Enriching Word Vectors with Subword Informationcited by 1,583
- 2019Survey on Publicly Available Sinhala Natural Language Processing Tools and Researchcited by 46
- 2022BERTifying Sinhala -- A Comprehensive Analysis of Pre-trained Language Models for Sinhala Text Classificationcited by 16
- 2024Aspect-Based Sentiment Analysis Techniques: A Comparative Studycited by 3
- 2024Instruct-DeBERTa: A Hybrid Approach for Aspect-based Sentiment Analysis on Textual Reviewscited by 2
- 2025Linguistic Analysis of Sinhala YouTube Comments on Sinhala Music Videos: A Dataset Studycited by 2
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Citing papers per year: 2026: 1.
1 paper.