By Malik Almaliki
Cyberhate against a person or a group based on their apparent identity, such as ethnicity, religion or nationality, on social media platforms is quickly growing and spreading. This has negative effects on both the online-generated content quality and the users of these platforms. Fortunately, the interest of computer science researchers in finding ways to stop cyberhate spread on social media platforms has been increasing recently. However, and to the best knowledge of the author, no studies have yet provided an overview and categorization of the various forms of conducted research on this subject, despite the increased interest in the subject. The author attempts to address this gap by performing a systematic mapping of the literature to generate an inclusive view of the subject in the last ten years (2012-2022). As a result, 274 primary studies were identified that fulfilled the devised criteria for including and excluding articles related to the context of this study. Following that, a grouping of these primary studies into categories based on their research type, contribution type, and research focus was conducted. The findings showed that the majority of the studies focused on offering cyberhate detection solutions. The findings also show that evaluation and validation of cyberhate detection solution, employing digital intervention approaches for reducing cyberhate dissemination by users, and the prevention and management of cyberhate propagation are all areas where research is lacking. The goal of this study is to assist practitioners and domain researchers in identifying current research gaps and promising areas for future research.
New York City, IEEE Access. 2023, 8pg
