  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.
