A Study of Algorithmic Resistance Behavior in Social Media Information Dissemination under Major Public Health Emergencies
[Purpose/Significance]In view of the numerous algorithmic negative problems caused by social media recommendation,it is necessary to study the algorithmic resistance behaviors of social media users under major public health emergencies for the emergency management and public opinion governance in China.[Method/Process]This paper constructed an influence mechanism model of algorithmic resistance behavior in social media information dissemination under major public health emergencies based on the Fogg behavioral model(FBM mod-el)and the risk information seeking and processing model(RISP model),and empirically examined it by question-naires and structural equation methods.[Result/Conclusion]The perceived risk variable in the trigger dimension positively affects negative emotional responses.The information insufficiency variable in the motivation dimension positively affects algorithmic resistance behavior.Algorithmic function perception in the capability dimension af-fects algorithmic resistance behavior through information insufficiency,and algorithmic FEAT perception directly affects algorithmic resistance behavior.This paper provides a new theoretical perspective and analytical framework for the study of algorithmic resistance behavior in social media information dissemination under major public health emergencies,and provides references for promoting social media algorithmic governance and emergency public opinion management of major public health emergencies.
major public health emergenciessocial mediainformation disseminationalgorithmic resis-tance
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