Cyberbullying Governance on Social Media: A Unified Framework from Content Identification to Intervention

Computer Science > Artificial Intelligence [Submitted on 26 May 2026] Cyberbullying Governance on Social Media: A Unified Framework from Content Identification to Intervention Yiting Huang, Wenting Zhu, Zekun Wang, Qingpo Yang, Yakai Chen, Zihui Xu, Yueyue Zhang, Sanchuan Guo, Xi Zhang The proliferation of social media platforms and online communities has inadvertently catalyzed the spread of cyberbullying, hate speech, and other forms of online toxicity, making the effective governance of such harm a critical societal and computational challenge. While significant strides have been made in automating content moderation, existing research predominantly treats cyberbullying governance as passive, isolated detection at the post level. This reductionist view overlooks the continuous behavioral dynamics of users, the structural diffusion of toxic events, and the critical need for proactive mitigation. To bridge these gaps, this paper proposes a unified full-lifecycle governance framework that shifts the paradigm of cyberbullying governance from isolated static detection toward integrated, continuous, and proactive moderation. Drawing on cyberbullying research and adjacent fields, we systematically synthesize the state-of-the-art literature across four interconnected stages: (1) Content Identification, (2) User and Behavior Modeling, (3) Diffusion Dynamics and Early Warning, and (4) Intervention and Governance. Furthermore, we review available datasets and evaluation practices, and discuss emerging challenges including multimodality, explainability, algorithmic fairness, and the dual-use risks of generative AI, providing a roadmap for future research toward a safer and more resilient digital ecosystem. Subjects: Artificial Intelligence (cs.AI); Social and Information Networks (cs.SI) Cite as: arXiv:2605.27584 [cs.AI]   (or arXiv:2605.27584v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2605.27584 Focus to learn more Submission history From: Yiting Huang [view email] [v1] Tue, 26 May 2026 18:53:19 UTC (3,074 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-05 Change to browse by: cs cs.SI References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)