Framework for Detection of Cyberbullying in Text Data Using Natural Language Processing and Machine Learning

View Sample PDF

Author(s): C. V. Suresh Babu (Hindustan Institute of Technology and Science, India), S. Kowsika (Hindustan Institute of Technology and Science, India), M. Sai Tejaswi (Hindustan Institute of Technology and Science, India), T. R. Janarakshani (Hindustan Institute of Technology and Science, India)and S. Mercysha Princy (Hindustan Institute of Technology and Science, India)
Copyright: 2023
Pages: 17
Source title: Cyber Security Policies and Strategies of the World's Leading States
Source Author(s)/Editor(s): Nika Chitadze (International Black Sea University, Georgia)
DOI: 10.4018/978-1-6684-8846-1.ch005

Keywords: Cyber and Network Security / Information Science Reference / Information Security & Privacy / Security & Forensics

Purchase

View Framework for Detection of Cyberbullying in Text Data Using Natural Language Processing and Machine Learning on the publisher's website for pricing and purchasing information.

Abstract

Cyberbullying is a huge problem online that affects young people and adults. It can lead to accidents like suicide and depression. There is a growing need to curate content on social media platforms. In the following study, the authors used data on two different forms of cyberbullying, hate speech tweets on Twitter, and ad hominem-based comments on Wikipedia forums. The authors use machine learning-based natural language processing and textual data to build models based on cyberbullying detection. They study three feature extraction methods and their four classifiers to determine the best method. The model achieves an accuracy of more than 90 degrees on the tweet data and more than 80 degrees on the Wikipedia data.

The IRMA Community

Research IRM

Framework for Detection of Cyberbullying in Text Data Using Natural Language Processing and Machine Learning

Purchase

Abstract

Related Content

IRMA Sponsors