Date of Submission
2025-03-26
Supervisor
Dr. Faisal Iradat, Assistant Professor, Department of Computer Science, School of Mathematics and Computer Science (SMCS)
Co-Supervisor
Dr. Nazim Taskin, Co-Supervisor, Boğaziçi University
Committee Member 1
Dr. Muhammad Waseem Iqbal, Examiner – I, Assistant Professor, Sultan Qaboos University, Oman
Committee Member 2
Dr. Tariq Mahmood, Examiner – II, Program Coordinator MS (CS) & MS (DS)
Degree
Master of Science in Computer Science
Department
Department of Computer Science
School
School of Mathematics and Computer Science (SMCS)
Keywords
Cyberbullying, Cyberbullying Detection, Machine Learning
Abstract
With the rise of communication technologies, cyberbullying has become a pressing problem. Taking into account the psychological traits and user profile of offenders to train cyberbullying detection models can improve the performance of these models and help authorities in implementing better detection and prevention systems, thus protecting potential victims from being bullied on online platforms. This thesis focuses on how information about the user can improve the detection accuracy of these cyberbullying detection models. This includes the psychological, emotional, and social state, all of which can be used as a training feature. An analysis of the results shows a positive relationship between psychology as a training feature and detection models, implying that incorporating this information can improve detection models and help reduce the problem of cyberbullying.
Document Type
Restricted Access
Submission Type
Thesis
Recommended Citation
Navaid, L. F. (2025). The Intersection of Technology & Human Behavior: The Use of Machine Learning for Cyberbullying Behavior with Psychological Insights (Unpublished Unpublished graduate thesis). Retrieved from https://ir.iba.edu.pk/etd-ms-cs/5
