A review on non-supervised approaches for cyberbullying detection

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Abstract

The current period is dominated by social networks in daily life. Despite the several efforts and research practices done to overcome the issue of cyberbullying, 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 computerbased methods has been performed 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.

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APA

Abou El-Seoud, S., Farag, N., & McKee, G. (2020). A review on non-supervised approaches for cyberbullying detection. International Journal of Engineering Pedagogy, 10(4), 25–34. https://doi.org/10.3991/ijep.v10i4.14219

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