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While deriving the Doppler formula for the observed frequency of a sound wave, it is assumed that the speed of sound in the medium is greater than the source's speed through it. When this condition is breached, a shock wave occurs.
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Rumor diffusion and convergence during the 3.11 earthquake: a twitter case study.

Misako Takayasu1, Kazuya Sato1, Yukie Sano2

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During emergencies, a city hall

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Area of Science:

  • Social Network Analysis
  • Computational Social Science
  • Information Diffusion Studies

Background:

  • Internet rumors and misinformation pose significant challenges during crises.
  • The rapid spread of unverified information can have detrimental societal impacts.
  • Effective strategies for combating misinformation during emergencies are crucial.

Purpose of the Study:

  • To analyze the diffusion and convergence of Internet rumors during emergencies.
  • To investigate the dynamics of a specific misinformation case following the Great East Japan Earthquake.
  • To develop and validate a computational model for simulating rumor propagation.

Main Methods:

  • Empirical analysis of Japanese tweets following the 2011 Great East Japan Earthquake.
  • Development of a stochastic agent-based model inspired by the SIR epidemic model.
  • Simulation of rumor diffusion dynamics using the agent-based model.

Main Results:

  • A single correction tweet from a city hall account achieved massive diffusion.
  • The agent-based model successfully reproduced observed rumor dynamics.
  • The model can estimate unobservable metrics like rumor infection rate and belief prevalence.

Conclusions:

  • Correction efforts, even from official sources, can be highly effective in mitigating misinformation.
  • Agent-based modeling provides a powerful tool for understanding and predicting rumor spread.
  • The developed model offers practical applications for estimating rumor diffusion in various emergency scenarios.