An Enhanced System to Detect Cyberbullying and Automate Reporting on Twitter Using Text Based Pattern Recognition Technique

Abstract: The increasing prevalence of cyberbullying on social media platforms necessitates effective detection and response mechanisms. This paper presents an enhanced system for detecting cyberbullying directed at politicians on Twitter and automating the reporting process. Utilizing advanced text-based pattern recognition techniques, the systePm identifies potentially harmful content and automatically reports it to a designated bot account for further action. We detail the system's architecture, the machine learning algorithms employed, and the performance of the system in terms of accuracy and speed. The proposed solution not only automates the detection and reporting processes but also contributes to safer online environments for politically active individuals.