ANUBHUTI: A Comprehensive Corpus For Sentiment Analysis In Bangla Regional Languages

TL;DR

This paper introduces ANUBHUTI, a large, annotated corpus of 10,000 sentences in Bangla regional dialects, designed to advance sentiment analysis in low-resource dialects with diverse content and high annotation quality.

Contribution

The creation of a comprehensive, annotated dataset for Bangla regional dialects, including dual thematic and emotion annotations, with quality assurance for sentiment analysis research.

Findings

High inter-annotator agreement achieved

Dataset covers diverse socio-political content

Enables improved sentiment analysis in Bangla dialects

Abstract

Sentiment analysis for regional dialects of Bangla remains an underexplored area due to linguistic diversity and limited annotated data. This paper introduces ANUBHUTI, a comprehensive dataset consisting of 10,000 sentences manually translated from standard Bangla into four major regional dialects Mymensingh, Noakhali, Sylhet, and Chittagong. The dataset predominantly features political and religious content, reflecting the contemporary socio political landscape of Bangladesh, alongside neutral texts to maintain balance. Each sentence is annotated using a dual annotation scheme: multiclass thematic labeling categorizes sentences as Political, Religious, or Neutral, and multilabel emotion annotation assigns one or more emotions from Anger, Contempt, Disgust, Enjoyment, Fear, Sadness, and Surprise. Expert native translators conducted the translation and annotation, with quality assurance performed via Cohens Kappa inter annotator agreement, achieving strong consistency across dialects. The dataset was further refined through systematic checks for missing data, anomalies, and inconsistencies. ANUBHUTI fills a critical gap in resources for sentiment analysis in low resource Bangla dialects, enabling more accurate and context aware natural language processing.