Bangla Sentiment Dataset

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.