Scopus Indexed Publications

Paper Details


Title
A Study of Cyber Bullying Classification Using Social Media and Texual Analysis Based on Machine Learning Approches
Author
Md. Shafiur Rahman Aronno, K.B.M. TAHMIDUZZAMAN, Md. Thoufiq Zumma, Rashed Prodhan,
Email
Abstract

In today's world, cyberbullying is a problem that is becoming more and more common, especially among teenagers and young people. The prevalence of social networking sites and other digital communication tools has made it simpler for offenders to harass their victims in secret and without repercussions. Natural language processing (NLP) methods have been used in recent years to categorize instances of cyberbullying and assist identify them. The language used in online conversations is examined using these approaches to look for trends and signs of cyberbullying behavior. The purpose of this study is to investigate how well NLP approaches can be used to recognize and categorize cyberbullying behavior. To provide a thorough knowledge of the many types of cyberbullying, the study will use a variety of data sources, including social media posts, chat logs, and other online conversations. Overall, this research will further our knowledge of the intricate nature of cyberbullying and shed light on the potential applications of NLP approaches to lessen its negative impacts.


Keywords
"Soft sensors , Anxiety disorders , Cyberbullying , Oral communication , Machine learning , Assistive technologies , Market research"
Journal or Conference Name
2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023
Publication Year
2023
Indexing
scopus