CYBERBULLYING DETECTION BY NLP

Abstract - Cyberbullying has become a growing concern with the rise of social media and online communication platforms. Manual moderation techniques are inadequate to handle the volume and complexity of abusive content. This study presents a cyberbullying detection model using Natural Language Processing (NLP) techniques. The system analyzes user-generated text to identify bullying behavior using pre-trained transformers and machine learning algorithms. Evaluation on benchmark datasets demonstrates high accuracy and low false positives. The research highlights the potential for real-time deployment and integration into social platforms to enhance digital safety.