Detection of Cyberbullying Using Machine Learning and Deep Learning Algorithms

Use of digital technologies lead to the development of cyberbullying and social media has become a major source for it compared to mobile phones, platforms such as gaming and messaging. Cyberbullying can take several forms that includes sexual remarks, threats, hate mails and posting false things about someone which can be seen and read by millions of people. Compared to traditional bullying, cyberbullying has a longer lasting effect on the victim which can affect them physically or emotionally or mentally or in all the forms. Number of suicides due to cyberbullying has increased in recent years and India is one among the four countries that has more number of cases in cyberbullying. Prevention of cyberbullying has become manda-tory in universities and schools due to rising cases since 2015. This paper aims to detect cyberbullying comments automatically using Machine learning and Deep learning techniques. Metrics such as accuracy, precision, recall and F1-score used to evaluate the model performance. It is found that Gated Recurrent Unit, a deep learning technique outperformed all the other techniques which are considered in this paper with an accuracy of 95.47%.