A Monitoring System for Cyber Bullying Activities using Stochastic Gradient Descent Classifier

Abstract

Abstract: Life has reached a stage where we cannot live without internet enabled technology. New devices and services are being invented continuously with the evolution of new technologies to improve our day-to-day lifestyle. At the same time, this opens many security vulnerabilities. Cybercrime may happen to any device/service at any time with worst ever consequences. Internet use today has a greater impact on young people than ever before. They view the internet and mobile phone networks as the two major communication frameworks that are crucial to our everyday lives and the formation of our identities. However, these technologies are often used improperly. Many internet users are the targets of bullying, which leaves the "target" completely perplexed. Cyberbullying is drastically increasing. The issue of cyberbullying is saddening because the system that enables communication and information flow is evolving into a risky "site" to visit. Cyberbullying affects people all across the world, not just in one nation. United States have begun to enact laws that are focused on cyberbullying. Other countries have adopted laws against bullying that apply to both regular bullying and cyberbullying. The internet gives users the option to browse anonymously and to create profiles with secret identities. Our proposed structure can significantly increase the existing methods detection capacity in actual social network scenarios while effectively making up for their drawbacks.