CHS: Small: Tracking and Unpacking Rumor Permutations to Understand Collective Sensemaking Online

本研究针对网路谣言的经验性与概念性问题，提出：（1）网路谣言在其一生中如何排列、分支或演化？(2)如何将离线环境中的谣言传播理论扩展到在线互动，以及哪些因素（技术和行为）影响这些动态，可能使在线环境成为信息流的独特环境？在应对危机的背景下，信息流动的动态尤为突出，因为社交媒体已成为正式和非正式通信基础设施的一个组成部分。 对网络谣言的进一步了解可以为危机应对者、记者和受灾害影响的公民提供沟通和信息收集策略，从而为检测、跟踪和应对错误信息和恶意谣言的传播提供创新解决方案。该项目有可能从根本上改变研究灾难期间在线集体行为的方法和理论。随着谣言在社交媒体上的发展和传播，追踪谣言的技术将帮助其他研究人员解决其他背景下的类似问题。为了回答这个项目的核心问题，研究人员将开发新的方法来识别和跟踪谣言，检测谣言故事中的线索以及谣言本身的排列。这将使研究人员能够绘制谣言轨迹，深入了解特定谣言和更广泛谣言类型的结构。使用这些地图，研究人员将采用互补的定量和定性分析，以及概念建模，以更好地了解在线集体意义的过程，通过透镜的谣言排列。定性分析将涉及分类和理解不同类型排列的基本原理，定量模型将帮助研究人员理解谣言中不同类型排列的总体模式，从而得出关于大规模集体意义构建的结论。 通过对社交媒体数据和访谈的分析，研究人员将改进和扩展新兴方法，以便对大规模在线互动进行混合方法分析。工作，以提高经验和概念的理解，网上谣言和集体意义制造将提供一个机会，以扩大经典理论的谣言失真的基础上的想法，平整，锐化和同化，并制定新的理论，网上复杂的故事的传播，将故事的动态和因素具体到在线空间。

This research addresses empirical and conceptual questions about online rumoring, asking: (1) How do online rumors permute, branch, and otherwise evolve over the course of their lifetime? (2) How can theories of rumor spread in offline settings be extended to online interaction, and what factors (technological and behavioral) influence these dynamics, perhaps making online settings distinct environments for information flow? The dynamics of information flow are particularly salient in the context of crisis response, where social media have become an integral part of both the formal and informal communication infrastructure. Improved understanding of online rumoring could inform communication and information-gathering strategies for crisis responders, journalists, and citizens affected by disasters, leading to innovative solutions for detecting, tracking, and responding to the spread of misinformation and malicious rumors. This project has the potential to fundamentally transform both methods and theories for studying collective behavior online during disasters. Techniques developed for tracking rumors as they evolve and spread over social media will aid other researchers in addressing similar problems in other contexts.To answer this project's core questions, researchers will develop novel methods to identify and track rumors over time, detecting threads within a rumor story as well as permutations in the rumor itself. This will allow researchers to map rumor trajectories, providing insight into the structure of specific rumors and broader rumor types. Using these maps, researchers will employ complementary quantitative and qualitative analysis, together with conceptual modeling, to better understand online collective sensemaking processes through the lens of rumor permutations. Qualitative analysis will involve classifying and understanding the underlying rationale for different types of permutations, and quantitative models will help researchers understand aggregate patterns of different kinds of permutations across rumors, to draw conclusions about collective sensemaking at scale. Through analysis of social media data and interviews, researchers will refine and extend emerging methods for doing mixed-method analysis on large-scale, online interaction. Work to enhance empirical and conceptual understandings of online rumoring and collective sensemaking will provide an opportunity to extend classical theories of rumor distortion based on ideas of leveling, sharpening and assimilation and to develop new theories for the spread of complex stories online, incorporating story dynamics and factors specific to online spaces.