Cyber Bullying Detection for Hindi-English Language Using Machine Learning

Abstract

Nowadays, the internet is the world’s biggest platform for communicating, connecting as well as sharing ideas, content, photos, videos, views, and daily updates globally. Social media is multifarious, which makes it extensive and interactive. Twitter, YouTube, Instagram, Linked In, Facebook and Whatsapp are some of the largest platforms. However, the enhancement of social connectivity often creates negative impacts on society that contribute to a couple of bad phenomena such as online abuse, harassment cyberbullying, cybercrime and online trolling. Cyberbullying frequently leads to serious mental and physical distress, particularly for women and children, and even sometimes force them to attempt suicide. Therefore, the identification of bullying text or message on social media has gained a growing amount of attention among researchers. Therefore our focus is to design and develop an effective technique to detect online abusive and bullying messages by merging Natural language processing and machine learning to develop a model that can detect offensive or hateful words in English and Hinglish language.

Keywords: Hindi, English, Cyberbully, Hindlish, Machine learning

JEL Classification: Y9