梳理社交网络中健康伪信息的IT应对方法，助力科研与实践。
Health Misinformation in Social Networks: A Survey of IT Approaches
- 从人工与自动两方面综述事实核查技术。
- 分析内容、传播特征与来源特征三类假新闻检测方法。
- 提供健康伪信息数据集与开源工具清单，适合安全与舆情研究者。
本文从信息技术视角全面综述社交网络中普遍存在的医疗伪信息问题。旨在系统梳理相关研究，帮助研究人员和从业者应对这一快速演进的领域。首先介绍人工与自动的事实核查方法；随后探讨基于内容、传播特征或来源特征的假新闻检测技术，以及遏制伪信息传播的缓解策略。此外，详细列出了多个健康伪信息数据集及公开可用工具。最后讨论当前面临的开放挑战与未来研究方向。
原文摘要 · Abstract (English)
In this paper, we present a comprehensive survey on the pervasive issue of medical misinformation in social networks from the perspective of information technology. The survey aims at providing a systematic review of related research and helping researchers and practitioners navigate through this fast-changing field. Specifically, we first present manual and automatic approaches for fact-checking. We then explore fake news detection methods, using content, propagation features, or source features, as well as mitigation approaches for countering the spread of misinformation. We also provide a detailed list of several datasets on health misinformation and of publicly available tools. We conclude the survey with a discussion on the open challenges and future research directions in the battle against health misinformation.
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