Bangla Sentiment Dataset
Description
The Bangla Sentiment Dataset is a curated collection of sentiment-rich textual data in Bangla, focused on recent and trending topics. This dataset has been compiled from diverse sources, including Bangladeshi online newspapers, social media platforms, and blogs, ensuring a wide spectrum of language styles and sentiment expressions. Key Features: Focus on Recent Topics: The dataset emphasizes contemporary issues, trending discussions, and popular topics in Bangladeshi society. This includes sentiments on political developments, social movements, entertainment, cultural events, and other recent happenings. Source Variety: Online Newspapers: Articles, editorials, headlines, and reader comments provide structured and semi-formal sentiment data. Social Media: Posts, tweets, and comments reflect informal, conversational language with high emotional expressiveness. Blogs: Opinion pieces and discussions offer detailed and context-rich sentiment content. Sentiment Labels: Each entry in the dataset is annotated with one of the following sentiment categories: Positive (1): Texts expressing happiness, agreement, or optimism. Negative (0): Texts reflecting criticism, disagreement, or pessimism. Neutral (2): Texts presenting balanced or factual statements with minimal emotional bias. Linguistic and Stylistic Diversity: The dataset captures a range of Bangla language variations, including: Formal and informal Bangla usage. Regional dialects. Transliterated Bangla (Banglish) commonly used on social media. Real-World Context: The inclusion of recent topics ensures that the dataset is relevant for analyzing public sentiment around current events and trends. This makes it particularly useful for real-time sentiment analysis applications. This dataset provides an invaluable resource for researchers and practitioners aiming to explore sentiment analysis in Bangla, with a special emphasis on modern-day relevance and real-world applicability.