Abstract
With the rise of communication technologies, cyberbullying has become a pressing problem. Victims of cyberbullying often find themselves struggling with the physical and psychological effects for many years to come, some even going as far as to take their own lives as a result. Thus, detecting and preventing cyberbullying is crucial. Machine learning and artificial intelligence models have been used for this purpose, however, there is room for improvement regarding considering context and training of these models on additional features. Taking into account the psychological traits and user profile of offenders to train detection can improve performance and help authorities in implementing better detection and prevention systems, thus protecting potential victims from being bullied on online platforms.
Recommended Citation
Lubaina, Navaid; Iradat, Faisal; and Taşkın, Nazım, "CYBERBULLYING DETECTION WITH MACHINE LEARNING & PSYCHOLOGY: A SYSTEMATIC REVIEW" (2025). CONF-IRM 2025 Proceedings. 20.
https://aisel.aisnet.org/confirm2025/20