Cyberbullying Detection using Machine Learning
Aaminah Ali, Adeel M. Syed
Abstract
It is an age of the Internet and electronic media, and social media platforms are one of the most frequently used communication medium nowadays. But some people use these sites for malicious purpose and among those negative aspects "Cyberbullying" is prevalent. Cyberbullying is a form of bullying done through electronic means and is used to insult or harm others. Many researchers have proposed solutions and strategies to overcome this menace, but sarcasm is one aspect of it that still needs to be touched. This study aims to highlight previous researchers and to propose an approach to detect cyberbullying along with the element of sarcasm included in it. The results proved that SVM classifier performed better than other classifiers.