A Review on Non-Supervised Approaches for Cyberbullying Detection
Samir Abou El-Seoud, Nadine Farag, Gerard McKee · International Journal of Engineering Pedagogy (iJEP) · 2020
The current period is dominated by social networks in daily life. Despite the several efforts and research practices done to overcome the issue, it still presents a problem. Despite the fact that social networks are useful for social gathering and communication, they also present new opportunities for harmful criminal acts. Cyber-harassment is an example that is enabled through the mistreatment and abuse of the internet as a means of harassing or bullying others virtually. To minimize these occurrences, research into computer-based methods has been per-formed to detect cyber-harassment. This literature survey shows that supervised learning methods were mostly used for cyber-bullying detection. Moreover, some non-supervised methods and other techniques have also shown to be effective in terms of accuracy towards cyber-bullying detection. This paper, therefore, surveys existing recent research on non-supervised techniques as well as it summarizes accuracy results obtained from several papers to discuss the significance of non-supervised learning approaches in comparison with traditional learning methods.