Journal ArticleOpen Access
Cyberbullying Detection on Social Networks Using Machine Learning Approaches
Authors
Author Affiliations
Jagannath University, Federation University
Published In2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)
Year2020
Citations116
Abstract
The use of social media has grown exponentially over time with the growth of the Internet and has become the most influential networking platform in the 21st century. 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. Online harassment attracts attention due to its strong negative social impact. Many incidents have recently occurred worldwide due to online harassment, such as sharing private chats, rumours, and sexual remarks. Therefore, the identification of bullying text or message on social…
View at Publisher
BORR does not host full-text PDFs. The button above takes you to the original publisher.