Cyberbullying: an interdisciplinary survey of the dark side of social networks

Cyberbullying is a growing digital threat with serious psychological and social consequences. This interdisciplinary survey examines its defining characteristics, impact on victims, and the challenges of detection and intervention. Drawing from technological, psychological, educational, and legal perspectives, the paper maps the landscape of current research and methods. From a technical standpoint, we highlight the use of artificial intelligence (AI) techniques—such as supervised machine learning, deep learning, natural language processing (NLP), and multimodal analysis—for content detection and behavioral pattern recognition. Social Network Analysis supports the detection of relational dynamics, while ethical considerations address issues like privacy, accountability, and moderation. The proposed framework is conceptual and not empirically validated. This review aims to support cross-disciplinary understanding and future research on practical implementation.