Cyberbully Retarder System using Machine Learning

Abstract

Covid-19 has switched almost every facet of life to online mode. Therefore, parents are forced to buy gadgets for their children for learning purposes. As a result, cyberbullying has also increased. Nowadays, youngsters get bullied online while using social media and playing online games. Everyday nearly thousands of users deal with bullying related to body shame, facial appearance, behavior, racism, sexual harassment, and other kinds of online bullying. To prevent this harassment, Machine learning algorithms are used to automatically detect the use of abusive words used by the bullies, and the developers will be notified if any type of abusive words are found and the necessary action can be taken. Moreover, a message will be sent if there is any abusive content in the chat. Therefore, the proposed method is efficient in identifying a cyber bullying activity on social media. This system will undoubtedly be useful as many students create social media accounts to keep track of their school life. Now that everything is online, this system proves beneficial in preventing cyberbullying.