AI Based Cyberbullying Detection and Prevention
Rohan Gupta, Ankit Kumar Singh, Utkarsh, Prachi Mittal, K R Radhika
Abstract
Cyberbullying In today's world, cyberbullying has spread like wildfire, disrupting both social harmony and personal relationships. It is undeniable that the rise in bullying and trolls on social media has had a psychological toll on individuals who are singled out. In response, the field of AI-based cyberbullying detection and prevention is examined in this paper. With an emphasis on Random Forest, SVM (the Support Vector Machine), and also Logistic Regression in particular, this study evaluates the efficacy of numerous machine learning techniques. This study offers a comprehensive grasp of how appropriate each algorithm is to solve cyberbullying through a detailed analysis of the advantages and disadvantages of each algorithm. It also advocates for the incorporation of these mechanisms with support groups and non-governmental organizations (NGOs) to advance social well-being.