Social media discourse on feminism: A dataset for sentiment analysis in bangla comments
Year: 2025
Type: data-paper
Abstract: Bangladesh is a socio-culturally diverse country where perspectives on women's freedom vary significantly. Social media sites are now important places for sharing feminist ideas through public comments and posts. This study offers a detailed collection of 6,830 comments in Bangla about feminism to help analyze public opinion. Most of this data comes from Facebook, with some also from Instagram and Twitter. Data collection involved systematic extraction from public groups and targeted hashtag searches, including (women's rights). Native Bangla speakers meticulously annotated each comment by hand to ensure that it was topical and to identify any abusive language. This manual validation procedure guarantees a high-quality dataset appropriate for the study of online gender-based violence in the Bangla language context, sentiment analysis, and abusive language analysis, among other machine learning and NLP tasks. In addition, comments were divided into three sentiment classes: neutral, negative, and positive. This allowed for thorough analysis of feminist discourse on Bangladeshi social media and supervised learning.
Source: Data in Brief
Institution: Southeast University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,220
OpenAlex ID: W7117128495