期刊名称：Journal of King Saud University @?C Computer and Information Sciences
印刷版ISSN：1319-1578
出版年度：2022
卷号：34
期号：7
页码：4099-4108
语种：English
出版社：Elsevier
摘要：Researchers around the world have been implementing machine learning as a method to detect cyberbullying text. The machine is trained using features such as variations in texts, through social media context and interactions in a social network environment. The machine can also identify and profile users through gender or use of hate speech. In this study, we analysed different types of mobile applications that manage cyberbullying. This study proposes a mechanism, which combines the best cyberbullying detection features to fill the gaps and limitations of existing applications. The results of the study have shown that the proposed mobile application records a higher accuracy in detecting cyberbully than other available applications.
