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Research on the dissemination mechanism of online rumors in public health events based on the SNITR model

Bibliographic Data

ID22066448
AuthorsMengna Zhang (0000-0003-4213-3584, Guizhou University of Finance and Economics), Xin Zhang (0000-0003-0184-5868, Guizhou University of Finance and Economics, corresponding author), Yuqing Chen (0000-0003-3832-3836, Guizhou University of Finance and Economics, corresponding author), Fuzhao Li (0009-0004-8341-5590, Guizhou University of Finance and Economics, corresponding author)
Year2026
Volume14
Pages1791115-1791115
Publication date2026-04-20
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2026.1791115
PMID42088251
OpenAlexW7154989972
LanguageEN
References cited19

During public health events, nodes on social networks that are aware of the truth may still actively disseminate rumors, thereby influencing the rumor propagation process. However, existing research has not yet taken into account the impact of transmitter nodes on rumor dissemination. Therefore, our study proposes an SNITR rumor propagation model that incorporates a rumor-transmitter mechanism. When rumor information emerges on social networks, susceptible users may neglect to propagate the received rumor information upon exposure (neglected nodes), some users may believe the rumors and spread them (infected nodes), while others may publicly state the truth to reduce the spread of rumors (transmitter nodes). Eventually, users will enter a recovered state and no longer participate in the rumor propagation process. By introducing the rumor-transmitter mechanism, a competitive coupling mechanism among different user groups is established. Additionally, the dynamics of the rumor propagation model are analyzed, the system's equilibrium points and basic reproduction number are calculated, and it is demonstrated that the equilibrium points are both locally and globally asymptotically stable. Finally, simulation experiments validate the effectiveness of the theoretical model and demonstrate that it aligns well with the intrinsic mechanisms of actual rumor propagation

Dissemination · Information Dissemination · Neglect · Rumor · Social media · Complex Network Analysis Techniques · Misinformation and Its Impacts · Opinion Dynamics and Social Influence

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Highly citedNo
Open DOIOpen Access
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