CricBakko: A New Bangla Dataset on Bangladesh Cricket for Sentiment Analysis
Sentiment analysis is a powerful tool for measuring public opinion on various topics. People Share their thoughts in different ways. Social media platforms such as Facebook and YouTube are widely used to express opinions on current topics, particularly trending subjects such as sports. Recently, research on sentiment analysis has grown rapidly. In the Bengali language, sentiment analysis is progressing and nowadays it is considered as a research interest. However, there are some barriers to sentiment analysis in the Bengali language such as the lack of a proper annotated dataset, managing lexicon such as part-of-speech, etc. Cricket is a famous sport in the world. It is also famous in Bangladesh. In this study, we collect comments from Facebook and YouTube where people share their opinions and emotions about Bangladesh cricket and its players. Unlike other comparable datasets that have been founded upon institutional sources such as newspapers, our dataset captures informal and emergent public sentiment. This study contributes significantly to the field of sentiment analysis research by introducing a novel Bangla dataset specifically designed for the domain of Bangladesh Cricket. This resource offers valuable data and insights for researchers, practitioners, and enthusiasts seeking to analyze sentiment across multiple domains including social media monitoring, fan research, and sports analytics.
Authors
- Bivas Biswas (ORCID: https://orcid.org/0000-0002-6101-5500)
- Md. Mushtaq Shahriyar Rafee (ORCID: https://orcid.org/0000-0001-8580-0821)
- Sumon Ahmed Masum
- M. Limon (ORCID: https://orcid.org/0000-0002-5900-2698)
- Md. Mahfujul Hasan
- Md. Shuhayel Alom Shanto
Institutions
- Shahjalal University of Science and Technology (BD)
- International Islamic University Chittagong (BD)
- Metropolitan University (BD)
- University of Chittagong (BD)
Publication Details
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1109/ncim65934.2025.11160196
- Primary Topic
- Sports Analytics and Performance
- Type
- article
- Field-Weighted Citation Impact
- 0.00