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Publication

Centralized, Parallel, and Distributed Information Processing during Collective Sensemaking

Peter Krafft, Kaitlyn Zhou, Isabelle Edwards, Kate Starbird, Emma Spiro. (2017). Centralized, Parallel, and Distributed Information Processing during Collective Sensemaking. ACM CHI Conference on Human Factors in Computing Systems (CHI).

Abstract

Widespread rumoring can hinder attempts to make sense of what is going on during disaster scenarios. Understanding how and why rumors spread in these contexts could assist in the design of systems that facilitate timely and accurate sensemaking. We address a basic question in this line: To what extent does rumor evolution occur (1) through reliance on a centralized information source, (2) in parallel information silos, or (3) through a web of complex informational interactions? We develop a conceptual model and associated analysis algorithms that allow us to distinguish between these possibilities. We analyze a case of rumoring on Twitter during the Boston Marathon Bombing. We find that rumor spreading was predominantly a parallel process in this case, which is consistent with a hypothesis that information silos may underlie the persistence of false rumors. Special attention towards detecting and resolving parallel information threads during collective sensemaking may hence be warranted.

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