THE EXPERIMENTAL CASE OF CYBERBULLYING DETECTION IN THE SOCIAL NETWORK

Authors

  • Ms. Saranya T, Nivetha A, Parthiban S, Vidhyakaran R, Vikashini B

Keywords:

Cyber bullying, Victims, Machine Learning, Natural Language Processing, Twitter, Natural Language Processing

Abstract

Cyberbullying is a ubiquitous social practice that can have a variety of severe psychological, behavioral, and health consequences for cyberbullying victims, according to this investigation. According to studies, cyberbullying happens all throughout the world. Understanding the characteristics and processes that lead to cyberbullying is crucial for treatments aimed at decreasing antisocial behavior online. Cyber bullying is a widespread problem on the internet that affects both teens and adults. It has resulted in misfortunes such as suicide and sadness. Content regulation on social media sites is becoming increasingly important. The following work combines data from two types of cyber bullying, hate speech tweets from Twitter and comments from Wikipedia forums focused on personal assaults, to create a model for detecting cyberbullying in text data using Natural Language Processing and Machine Learning. To determine the optimum technique, three feature extraction approaches and four classifiers are investigated.

Published

2022-06-30

How to Cite

Ms. Saranya T, Nivetha A, Parthiban S, Vidhyakaran R, Vikashini B. (2022). THE EXPERIMENTAL CASE OF CYBERBULLYING DETECTION IN THE SOCIAL NETWORK. International Journal of Advanced Engineering Science and Information Technology, 10(6). Retrieved from http://ijaesit.com/index.php/home/article/view/101