Cyberbullying Detection: Exploring Datasets, Technologies, and Approaches on Social Media Platforms

• URL: http://arxiv.org/abs/2407.12154v1
• Date: Wed, 22 May 2024 04:58:20 GMT
• Title: Cyberbullying Detection: Exploring Datasets, Technologies, and Approaches on Social Media Platforms
• Authors: Adamu Gaston Philipo, Doreen Sebastian Sarwatt, Jianguo Ding, Mahmoud Daneshmand, Huansheng Ning,
• Abstract summary: This paper presents a comprehensive systematic review of studies conducted on cyberbullying detection. It explores existing studies, proposed solutions, identified gaps, datasets, technologies, approaches, challenges, and recommendations.
• Score: 3.235558067839701
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Cyberbullying has been a significant challenge in the digital era world, given the huge number of people, especially adolescents, who use social media platforms to communicate and share information. Some individuals exploit these platforms to embarrass others through direct messages, electronic mail, speech, and public posts. This behavior has direct psychological and physical impacts on victims of bullying. While several studies have been conducted in this field and various solutions proposed to detect, prevent, and monitor cyberbullying instances on social media platforms, the problem continues. Therefore, it is necessary to conduct intensive studies and provide effective solutions to address the situation. These solutions should be based on detection, prevention, and prediction criteria methods. This paper presents a comprehensive systematic review of studies conducted on cyberbullying detection. It explores existing studies, proposed solutions, identified gaps, datasets, technologies, approaches, challenges, and recommendations, and then proposes effective solutions to address research gaps in future studies.

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