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

本研究解决了关于网络谣言的实证和概念性问题，提出了以下问题：(1)网络谣言在其一生中是如何排列、分支和演变的？(2)如何将线下谣言传播的理论扩展到线上互动，哪些因素（技术和行为）影响了这些动态，可能使线上环境成为不同的信息流环境？在危机应对的背景下，信息流的动态尤为突出，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。提高对网络谣言的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，从而为发现、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。这个项目有可能从根本上改变灾害期间在线研究集体行为的方法和理论。跟踪谣言在社交媒体上演变和传播的技术将有助于其他研究人员在其他情况下解决类似问题。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。这将允许研究人员绘制谣言轨迹，提供对特定谣言结构和更广泛谣言类型的洞察。利用这些地图，研究人员将采用互补的定量和定性分析，以及概念建模，通过谣言排列的镜头更好地理解在线集体意义制造过程。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了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的结论。通过分析社交媒体数据和访谈，研究人员将完善和扩展新兴的方法，对大规模的在线互动进行混合方法分析。加强对网络谣言和集体语义的实证和概念理解的工作将提供一个机会，以平衡、锐化和同化的思想为基础，扩展谣言扭曲的经典理论，并为复杂故事的在线传播发展新的理论，将故事动态和特定于网络空间的因素结合起来。

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.