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

University Of Washington, Seattle WA

Investigators

Abstract

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.