AI – DRIVEN CYBERBULLYING DETECTION AND PREVENTION SYSTEM USING NLP

Cyberbullying has become a major concern on social media platforms, threatening users' mental health and online safety. An AI-powered system for detecting and preventing cyberbullying is essential for fostering secure digital communication. By using Natural Language Processing (NLP) and Machine Learning (ML), such a system can monitor user comments in real time and identify harmful, abusive, or offensive language. When potentially harmful content is detected, the system sends an automatic warning to the sender, letting them know their message might be inappropriate. This gives them the chance to edit or reconsider before sending. If the sender proceeds, the message is blocked from reaching the receiver, preventing emotional harm and creating a safer online environment. The system uses text preprocessing, tokenisation, and feature extraction techniques, such as TF-IDF or word embeddings, followed by classification methods like Logistic Regression and Long Short-Term Memory (LSTM) models, for accurate predictions. By employing AI and NLP for real-time monitoring and intervention, this system effectively reduces cyberbullying and promotes a more positive and secure online environment.