Student-People Mass Uprising Public Sentiments Dataset (July Revolution, Bangladesh, 2024)

The Student-People Mass Uprising Public Sentiments Dataset comprises 4,200 manually collected and labeled Bangla-language social media comments related to the July Revolution in Bangladesh, 2024. Sourced from Facebook, YouTube, and Twitter (X), the dataset includes an equal distribution of 1,400 positive, 1,400 negative, and 1,400 neutral comments to ensure class balance. Each comment was annotated based on clear sentiment criteria, reflecting real-world public reactions to a significant political event. This dataset is structured in CSV format and is intended for use in sentiment analysis, natural language processing, and low-resource language research. It can serve as a benchmark for developing and evaluating machine learning models for Bangla text classification and social media sentiment analysis. Recommended Use:Academic and applied research in sentiment analysis, Bangla NLP, and social media mining. To use this dataset, you must provide appropriate credit by citing the following paper: Hossen, M. S., Shaha, P., & Saiduzzaman, M. (2025). Social Media Sentiments Analysis on the July Revolution in Bangladesh: A Hybrid Transformer Based Machine Learning Approach. In Proceedings of the 17th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). IEEE. Bibtex Entry for LaTeX users: @inproceedings{hossen2025july, author = {Hossen, Md Sabbir and Shaha, Pabon and Saiduzzaman, Md}, title = {Social Media Sentiments Analysis on the July Revolution in Bangladesh: A Hybrid Transformer Based Machine Learning Approach}, booktitle = {Proceedings of the 17th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)}, year = {2025}, publisher = {IEEE} }