An Enhanced Machine Learning Framework for Cyberbullying Detection in Social Media Text Messages

Abstract

The rapid usage of internet makes it easy for the people to communicate across the globe and use the social media. Cyberbullying is considered to be a form of online harassment that creates harsh consequences like mental health issues, social isolation and even suicide. Nowadays Cyber bullying on social media has become a widespread issue in digital age that causes harmful and negative impacts on people. This paper mainly focuses on finding those cyberbullying messages employing language processing methods thereby processing textual data and few machine learning algorithms to characterize them and detect correlating them with the preprocessed data. From the observations, it is noted that when compared to all the other machine learning used the gradient descent method seems to perform better and with the prediction results a warning message is sent to the sender if the text data in the social media contains bullying kind of messages. Also, a block notification is sent to the receiver asking him to block the text from the sender.