Automated Cyberbullying Activity Detection using Machine Learning Algorithm

Abstract

Cyberbullying is the use of technology to harass, intimidate, or harm another person by making hurtful comments, sending threatening messages to humiliate someone in social media. It is important to recognize the signs of cyberbullying activities and takes steps to prevent it. Automated Machine Learning algorithms and Text mining concepts for detecting and classifying bullying messages in social media environment. The abusive texts are clustered using Multinomial Naïve Bayes, LinearSVC, Logistic Regression, K-Nearest neighbour to build a classifier from training datasets. Implementation uses Suspicious-communications-on-social-platforms dataset.