Soft Computing Techniques for Detecting Cyberbullying in Social Multimedia Data

Jing Y. Haowei M. Ansari A.S. Sucharitha G. Omarov B. Kumar S. Mohammadi M.S. Alyamani K.A.Z.
28 September 2023 Association for Computing Machinery

Journal of Data and Information Quality
2023 #15 Issue 3

Cyberbullying is a form of abuse, manipulation, or humiliation directed against a single person via the Internet. CB makes use of nasty Internet comments and remarks. It occurs when someone publicly mocks, insults, slanders, criticizes, or mocks another person while remaining anonymous on the Internet. As a result, there is a rising need to create new methods for sifting through data on social media sites for symptoms of cyberbullying. The goal is to lessen the negative consequences of this condition. This article discusses a soft computing-based methodology for detecting cyberbullying in social multimedia data. This model incorporates social media data. Normalization is performed to remove noise from data. To improve a feature, the Particle Swarm Optimization Technique is applied. Feature optimization helps to make cyberbullying detection more accurate. The LSTM model is used to classify things. With the help of social media data, the PSO LSTM model is getting better at finding cyberbullying. The accuracy of PSO LSTM is 99.1%. It is 2.9% higher than the accuracy of the AdaBoost technique and 10.4% more than the accuracy of the KNN technique. The specificity and sensitivity of PSO-based LSTM is also higher in percentage than KNN and AdaBoost algorithm.

cyberbullying detection , denoising , feature optimization , normalization , PSO , Social multimedia data

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Faculty of Computer Science and Information Technology, University of Malaya, Malaysia
Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Malaysia
Department of Informa- Tion Technology, College of Computer and Information Sciences, Majmaah University, Al-Majmaah, 11952, Saudi Arabia
Department of Electronics and Communication Engineering, Institute of Aeronautical Engineering, Hyderabad, India
International University of Tourism and Hospitality, Turkistan, Kazakhstan
Department of Computer Science and Engineering, Maharaja Surajmal Institute of Technology, New Delhi, India
Department of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia
Applied College, Abqaiq Branch, King Faisal University, P.O. Box 4000, Al-Ahsa, 31982, Saudi Arabia

Faculty of Computer Science and Information Technology
Department of Mechanical Engineering
Department of Informa- Tion Technology
Department of Electronics and Communication Engineering
International University of Tourism and Hospitality
Department of Computer Science and Engineering
Department of Information Technology
Applied College

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