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| Risk Identification and Early Warning Model of Social Media Network Public Opinion in Emergencies |
| Li Yueqi1,3, Wang Xiwei1,2,3, Wang Nan'axue2, Wang Xiaotian1,3 |
1.School of Business and Management, Jilin University, Changchun 130022
2.Institute of National Development and Security Studies, Jilin University, Changchun 130022
3.Research Center for Big Data Management, Jilin University, Changchun 130022 |
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Abstract Global natural disasters and public health emergencies occur frequently, and the risk crisis of online public opinion in social media is increasing gradually. The key point in emergency management is how to effectively identify and alert the risk of online public opinion in social media in emergencies. In this study, based on the ISM-BN model, the public opinion risk identification and early warning model of emergency in social media network is constructed to strengthen the judgment of key issues and need of risk for early warning. We built the knowledge database of social media risk of emergencies through a knowledge map. We used interpretative structural modeling (ISM) to identify the causal path and hierarchical relationship of the risk factors of social media network public opinion in emergencies. The Bayesian network (BN) model was used to warn about the social media risks of emergencies. We achieved the closed-loop decision-making process of emergency risk knowledge acquisition, knowledge analysis and early warning decision. This study provides a new theory and research method of social media risk management in the emergency environment, and public opinion risk identification and early warning decision support for related public opinion supervision structures.
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Received: 08 April 2022
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