Analyzation and detection of cyberbullying: A Twitter based Indian case study

Abstract

Social networking sites like Facebook and Twitter specially involves large population connected worldwide. Though these social networks aim to bring people from around the world together yet it has its own cons associated with it. With the increase in these Social Networks there is an exponential increase in cybercrimes on these sites. Cyberbullying or Trolling is one such crime where victim is bullied with abuses, personal remarks, false claims and sarcasm on social networking sites and sometimes is traumatized to great extent. There have been many cyberbullying detection methods and systems already developed to cater to the problem but major concern lies on the fact that nearly 80%–90% users on such sites are Indians owing to one of most populous countries in the world, they use Hinglish (Hindi written in English) to communicate mostly on social networking sites majorly Facebook and Twitter. Our research aims at analyzing Cyberbullying content based on Hinglish tweets on one such social network that is Twitter. We analyzed tweets based on textual analysis and performed classification also. Through this we concluded our findings and future scope of work for detection of Cyberbullying on more complex data.