A THEORETICAL MODEL OF FALSE INFORMATION CONTROL

Yu Zhang, Nicolã“ Vallarano, Fanyuan Meng and Claudio J. Tessone
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Yu Zhang: Blockchain and Distributed Ledger Technologies, Institute of Informatics, University of Zürich, Andreasstrasse 15, 8050, Zürich, Switzerland
Nicol㓠Vallarano: Blockchain and Distributed Ledger Technologies, Institute of Informatics, University of Zürich, Andreasstrasse 15, 8050, Zürich, Switzerland
Fanyuan Meng: ��Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, Zhejiang, P. R. China
Claudio J. Tessone: Blockchain and Distributed Ledger Technologies, Institute of Informatics, University of Zürich, Andreasstrasse 15, 8050, Zürich, Switzerland

Advances in Complex Systems (ACS), 2025, vol. 28, issue 07, 1-19

Abstract: When considering a specific event, news that accurately reflects the ground truth is deemed as real information, while news that deviates from the ground truth is classified as false information. False information often spreads fast due to its novel and attention-grabbing content, threatening our society. By extending the Susceptible-Infected (SI) model, our research offers analytical decision boundaries that enable effective interventions to get desirable results, even when intermediate functions cannot be analytically solved. When assessing intervention costs using the model, the results indicate that the sooner we intervene, the lower the overall intervention cost tends to be.

Keywords: Real information; false information; SI model; intervention; analytical decision boundary (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0219525925500122

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