Rumor Diffusion and Convergence during the 3.11 Earthquake: A Twitter Case Study

• Published in: PLoS ONE Vol. 10; no. 4; p. e0121443
• Main Authors: 佐野 幸恵, Takayasu Misako, Sato Kazuya, Sano Yukie, Yamada Kenta, Miura Wataru, Takayasu Hideki
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.04.2015; Public Library of Science (PLoS)
• Subjects: Aftershocks; Algorithms; Blogging; Case reports; Case studies; Communication; Computer Simulation; Convergence; Diffusion; Earthquakes; Economic summit conferences; Emergencies; Empirical analysis; Engineering; Epidemics; Humans; Information Dissemination; Interdisciplinary aspects; Internet; Japan; Mathematical models; Science; Seismic activity; Social Media; Social networks; Stochasticity; Studies; Japan; New York; United States > US; Tokyo Bay
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0121443

We focus on Internet rumors and present an empirical analysis and simulation results of their diffusion and convergence during emergencies. In particular, we study one rumor that appeared in the immediate aftermath of the Great East Japan Earthquake on March 11, 2011, which later turned out to be misinformation. By investigating whole Japanese tweets that were sent one week after the quake, we show that one correction tweet, which originated from a city hall account, diffused enormously. We also demonstrate a stochastic agent-based model, which is inspired by contagion model of epidemics SIR, can reproduce observed rumor dynamics. Our model can estimate the rumor infection rate as well as the number of people who still believe in the rumor that cannot be observed directly. For applications, rumor diffusion sizes can be estimated in various scenarios by combining our model with the real data.