FIGHT BACK CYBERBULYYING WITH NLP ON SNS USING CODE TEXT APPROACH

FIGHT BACK CYBERBULYYING WITH NLP ON SNS USING CODE TEXT APPROACH

Kunal Gupta1, Kanchan Ghule2, Ankita Dhondge3*, Shruti Dive4, Aniruddha S. Rumale5

1,2,3,4, Student, 5Professor, Information Technology Department, Sandip Institute Of Technology And Research Centre, Nashik, India

ABSTRACT: This research paper is about the important problem of rising hate and offensive Contents made against people or communities on social media is addressed by this proposed system. With the increasing use of social media, cyberbullying behaviour has received more and more attention. Cyberbullying may cause many serious and negative impacts on a person’s life and even lead to teen suicide. To reduce and stop cyberbullying, one effective solution is to automatically detect bullying content based on appropriate machine learning and natural language processing techniques. The impacts of cyber bullying on social media are horrifying, sometimes leading to the death of some unfortunate victims. The behaviour of the victims also changes due to this, which affects their Emotions, self-confidence and a sense of fear is also seen in such people. Thus, a complete solution is required for this problem. Cyber bullying needs to stop. The problem can be tackled by detecting and preventing it by using a machine learning approach, this needs to be done using a different perspective.

Keywords: Hate Speech; Social Networking Site; Natural Language Processing; Text Classification; Machine Learning