The use of social media across all demographic groups has brought the harmful nature of cyberbullying into sharper focus. Detecting cyberbullying on social media platforms has become widely researched in Information Systems (IS) research. However, previous literature has primarily focused on designing technical detection tools to classify cyberbullying, overlooking connected contextual, social, and psychological dynamics between users. Therefore, this research summarizes existing cyberbullying analysis methods, focusing on social and technical aspects. It evaluates existing approaches from a systematic literature review to identify suitable strategies to improve cyberbullying detection. We identified thirty-one fundamental articles in this context. We extracted three categories to address improvement potential: detection methods and technologies, socio-behavioural perspectives for cyberbullying, and regulatory and contextual influences. Based on our findings, we provide a research agenda and recommendations for designing strategies to detect cyberbullying.