Cyberbullying Prevention: AI-Based Tools for Detection and Mitigation of Online Harassment

Abstract: This study looks at the growing issue of cyberbullying and the possibilities of AI-based technologies as a preventative approach. The study addresses the problem of traditional detection methods failing to keep up with the severity of bullying and the quick changes in online communication. How effectively can AI-based solutions detect and prevent cyberbullying on various social media sites is the primary study question. The research will employ a mixed-methods approach, combining a quantitative study of a simulated dataset with a comprehensive literature evaluation of existing AI content moderation solutions. The study will also include a qualitative component, like a case study, to evaluate the effectiveness and user experience of a specific AI-based application. Significant findings should demonstrate that while AI can significantly improve detection speed and accuracy, managing the nuances and context of online communication requires a hybrid approach that combines AI and human monitoring. The significance of this research lies in its ability to direct the development of more useful and effective technologies, which will eventually lead to safer online environments and less psychological harm from cyberbullying.