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The public opinion dissemination and evolution of food safety scandals

A case study from China

Bibliographic Data

ID22093069
AuthorsWeihuan Su (0000-0002-6250-8702, Shanxi University of Finance and Economics), Xiaodong Guo (0000-0003-2180-1985, Wuhan University of Technology, corresponding author)
Year2026
Volume10
Publication date2026-01-12
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Communication (JOURNAL)
Journal identifiersISSN: 2297-900X • E-ISSN: 2297-900X
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fcomm.2025.1715575
OpenAlexW7122590334
LanguageEN
References cited35

Background Food safety scandals pose severe threats to public health and social stability, often triggering widespread emotional reactions and disruptive public opinion crises. Understanding the mechanisms driving public opinion evolution in such scenarios is crucial for effective crisis management. Method To investigate these mechanisms, we developed the HK-SNPR model, which incorporates differentiated dissemination propensities. The model was applied to analyze public opinion data from the "McDonald's relabeling expired food" incident in China. Result The analysis revealed that negative opinions from high-influence users are most likely to provoke large-scale dissemination of public sentiment. Authoritative individuals exerted stronger influence than professional experts. Furthermore, the interaction between incident severity and individual involvement significantly steered the evolution of public opinion. Additionally, positive opinions played a critical yet asymmetric role, serving as a key leverage point for accelerating the attenuation of public opinion crises. Conclusion These findings provide important insights for the effective management and control of public opinion related to food safety scandals, highlighting the pivotal influence of key user groups and the stabilizing potential of positive information

China · Dissemination · Food safety · Information Dissemination · Opinion leadership · Public opinion · Social media · Data-Driven Disease Surveillance · Public Relations and Crisis Communication · Risk Perception and Management

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