Threatening Language Detection

Threatening language detection aims to automatically identify online abusive and threatening text, a crucial task given the proliferation of harmful content on social media. Current research heavily focuses on developing and comparing machine learning models, including Support Vector Machines and transformer architectures like BERT, particularly for low-resource languages like Urdu where data is scarce. The field's significance lies in its potential to improve online safety and content moderation, while also advancing natural language processing techniques for multilingual applications. High accuracy remains a challenge, especially in distinguishing threats from non-threatening language.