[论文解读] The Web of False Information: Rumors, Fake News, Hoaxes, Clickbait, and Various Other Shenanigans

Savvas Zannettou, Michael Sirivianos+2 more|arXiv (Cornell University)|Apr 10, 2018

Misinformation and Its Impacts参考文献 167被引用 61

一句话总结

该论文提出了网络虚假信息生态系统的分类，并综述了关于用户感知、传播、检测与政治性虚假信息的文献，指出差距与未来方向。

ABSTRACT

A new era of Information Warfare has arrived. Various actors, including state-sponsored ones, are weaponizing information on Online Social Networks to run false information campaigns with targeted manipulation of public opinion on specific topics. These false information campaigns can have dire consequences to the public: mutating their opinions and actions, especially with respect to critical world events like major elections. Evidently, the problem of false information on the Web is a crucial one, and needs increased public awareness, as well as immediate attention from law enforcement agencies, public institutions, and in particular, the research community. In this paper, we make a step in this direction by providing a taxonomy of the Web's false information ecosystem, comprising various types of false information, actors, and their motives. We report a comprehensive overview of existing research on the false information ecosystem by identifying several lines of work: 1) how the public perceives false information; 2) understanding the propagation of false information; 3) detecting and containing false information on the Web; and 4) false information on the political stage. In this work, we pay particular attention to political false information as: 1) it can have dire consequences to the community (e.g., when election results are mutated) and 2) previous work show that this type of false information propagates faster and further when compared to other types of false information. Finally, for each of these lines of work, we report several future research directions that can help us better understand and mitigate the emerging problem of false information dissemination on the Web.

研究动机与目标

• 在网络上提出虚假信息类型、参与者和动机的分类。
• 总结四条研究线上的现有研究：用户感知、传播动力学、检测/遏制，以及政治性虚假信息。
• 突出差距并提出未来研究方向，以减缓网络上的虚假信息传播。
• 强调政治性虚假信息的重要性及其潜在社会影响。

提出的方法

• 基于广泛的文献研究，开发一个关于虚假信息（类型、参与者、动机）的结构化类型学。
• 提供对所识别研究线中先前工作的全面概述。
• 特别关注政治性错误信息及其独特的影响和含义。
• 提供已识别的差距和未来研究方向，以理解和减缓虚假信息传播。

实验结果

研究问题

• RQ1 网络上有哪些各种类型和实例的虚假信息及其特征？
• RQ2 传播虚假信息的参与者是谁，他们的动机是什么？
• RQ3 主要的研究虚假信息的工作线（感知、传播、检测/遏制、政治）有哪些，以及存在的差距在哪里？
• RQ4 在政治语境中，虚假信息如何表现和传播，与其他类型相比有何不同？

主要发现

• 识别并分类出八种虚假信息类型：Fabricated, Propaganda, Conspiracy Theories, Hoaxes, Biased/one-sided, Rumors, Clickbait, and Satire News.
• 包含多样化的传播者，包括 Bots, Criminal/Terrorist Organizations, Activist/Political Organizations, Governments, Hidden Paid Posters, State-sponsored Trolls, Journalists, Useful Idiots, True Believers, and Trolls.
• 虚假信息背后的动机包括 Malicious Intent, Influence, Sow Discord, Profit, Passion, and Fun.
• 论文总结了跨平台（Twitter、Facebook、以及其他）用户感知的多项研究，以及数据分析、问卷调查、众包等方法。
• 传播研究按平台（Twitter、Facebook、其他）和方法（流行病学/统计建模、数据分析、可视化系统）进行分类。
• 作者强调政治领域特别具有影响力，并回顾相关工作，概述进一步研究和减缓策略的需要。