A Machine Learning and Community-Driven Approach for Feminist Cyber Resistance Framework to Mitigate Online Gender-Based Violence
Bala Gangadhara Gutam, Subhash Chandra Mouli D, J. Naveen Kumar, S. Dilli Babu, J Suresh Babu, Mukesh Kumar · 2025
This paper introduces a new approach, the Feminist Cyber Resistance Framework (FCRF), in the fight against Online Gender-based Violence (OGBV) through the collaborative practices of machine learning (ML), sentiment analysis and community collaboration. FCRF strives to: find harmful information, mitigate its impact in real-time, and empower under-represented communities using more inclusive digital methods. Validated with a dataset containing 10,000 marked postings, the framework was able to achieve detection accuracy (91.5%), precision (89.8 %), and to reduce the amount of time to flag a posting by 40% compared to human flagging methods. In addition to this, 85% of community members rated the framework positively on transparency and inclusion! The findings reaffirm FCRF as an essential tool for combating OGBV, fostering digital equality, and enabling safer circles on the internet for women.