[论文] Cyberbullying Governance on Social Media: A Unified Framework fro...

论文概要

研究领域: AI
作者: Yiting Huang, Wenting Zhu, Zekun Wang, et al.
发布时间: 2026-05-28
arXiv: 2605.27584

中文摘要

社交媒体平台和在线社区的激增无意中助长了网络欺凌、仇恨言论和其他形式的有毒内容的传播,使有效治理成为关键的社会和计算挑战。虽然在自动化内容审核方面已取得显著进展,但现有研究主要将网络欺凌治理视为帖子层面的被动、孤立检测。这种还原论视角忽视了用户的持续行为动态、有毒事件的结构化扩散,以及主动缓解的关键需求。本文提出了一个统一的全生命周期治理框架,将网络欺凌治理范式从孤立的静态检测转向集成化、持续化和主动化的审核。基于网络欺凌研究及相关领域,系统综合了四个相互关联阶段的最新文献:(1)内容识别,(2)用户与行为建模,(3)扩散动态与早期预警,(4)干预与治理。此外还回顾了可用数据集和评估实践,并讨论了多模态、可解释性、算法公平性和生成式AI双重用途风险等新兴挑战。

原文摘要

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 ...

自动采集于 2026-05-29

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