Investigating the Public Sentiment in Major Public Emergencies Through the Complex Networks Method: A Case Study of COVID-19 Epidemic

Yang, Guang; Wang, Zhidan; Lin, Chen

doi:10.3389/fpubh.2022.847161

Cited by 3 publications

(1 citation statement)

References 42 publications

(41 reference statements)

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“…Cheng et al [10] found that secondary disasters of major emergencies can have an impact on international oil prices. Yang et al [11] concluded that major emergencies can seriously affect the public's emotions and cause a certain amount of panic. Similarly, De las Heras-Pedrosa et al [12] argued that major emergencies can also have serious psychological effects on the public.…”

Section: Related Workmentioning

confidence: 99%

Dynamics analysis and optimal control study of uncertain information dissemination model triggered after major emergencies

Li,

Sun

et al. 2024

Front. Phys.

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In order to effectively prevent and combat online public opinion crises triggered by major emergencies, this paper explores the dissemination mechanism of uncertain information on online social platforms. According to the decision-making behavior of netizens after receiving uncertain information, they are divided into eight categories. Considering that there will be a portion of netizens who clarify uncertain information after receiving it, this paper proposes a SEFTFbTbMR model of uncertain information clarification behavior. The propagation dynamics equations of the model are given based on the theory of differential equations, the basic regeneration number R0 of the model is calculated, and the existence and stability of the equilibrium point of the model are analyzed. The theoretical analysis of the model is validated using numerical simulation software, and sensitivity analysis is performed on the parameters related to R0. In order to reduce the influence caused by uncertain information, the optimal control strategy of the model is proposed using the Hamiltonian function. It is found that the dissemination of uncertain information among netizens can be suppressed by strengthening the regulation of social platforms, improving netizens’ awareness of identifying the authenticity of information, and encouraging netizens to participate in the clarification of uncertain information. The results of this work can provide a theoretical basis for future research on the uncertain information dissemination mechanism triggered by major emergencies. In addition, the results can also provide methodological support for the relevant government departments to reduce the adverse effects caused by uncertain information in the future.

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Section: Related Workmentioning

confidence: 99%

Dynamics analysis and optimal control study of uncertain information dissemination model triggered after major emergencies

Li,

Sun

et al. 2024

Front. Phys.

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A Real-Time Impact Study of New Product Release on Theme Park Brand Reputation: Using Social Media Data from Shanghai Disneyland

Deng,

Liu

2024

Lecture Notes on Data Engineering and Communications Technologies

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Public Attitudes Towards Violence Against Doctors: Sentiment Analysis of Chinese Users (Preprint)

Zheng,

Tian,

Chen

et al. 2024

Preprint

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BACKGROUND Violence against doctors attracts the public’s attention both online and in the real world. Understanding the change in public opinion is essential to monitor public sentiment and make strategies to comfort the public’s emotions. OBJECTIVE This study aims to quantify the difference in public sentiment according to online public opinion life cycle theory and describe an evolution of public sentiment during a high-profile violence against doctors’ crisis in China. METHODS This study used the term frequency-inverse document frequency (TF-IDF) algorithm to extract key terms and created keyword clouds from textual comments. The Latent Dirichlet Allocation (LDA) topic model was employed to analyze the thematic evolution within public sentiment. The integrated Chinese Sentiment Lexicon was used to analyze the evolution of sentiments in the collected data. RESULTS 12,775 valid comments were collected on public opinion on Sina Weibo in China. Thematic and sentiment analyses showed that the public’s sentiments were highly negative during the outbreak period (Disgust: 33.52%, Anger: 22.32%), then smoothly changed to positive and negative during the spread period (Sorrow: 34.45%, Joy: 32.46%), and tended to be rational and peaceful during the decline period (Joy: 32.71%, Sorrow: 27.98%). However, no matter how emotions change, the leading tone of each period contains a large number of negative sentiments. CONCLUSIONS This study simultaneously examined the dynamics of theme change and sentiment evolution in crises involving violence against doctors. It discovered that public sentiment varied in tandem with the theme shifts, yet the dominant sentiment from the initial stage of public opinion prevailed throughout. This finding, distinguished from prior research, underscored the enduring impact of initial public sentiment. The results offered valuable insights for medical institutions and authorities, suggesting the need for tailored risk communication strategies responsive to the evolving themes and sentiments at different stages of a crisis.

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Investigating the Public Sentiment in Major Public Emergencies Through the Complex Networks Method: A Case Study of COVID-19 Epidemic

Cited by 3 publications

References 42 publications

Dynamics analysis and optimal control study of uncertain information dissemination model triggered after major emergencies

Dynamics analysis and optimal control study of uncertain information dissemination model triggered after major emergencies

A Real-Time Impact Study of New Product Release on Theme Park Brand Reputation: Using Social Media Data from Shanghai Disneyland

Public Attitudes Towards Violence Against Doctors: Sentiment Analysis of Chinese Users (Preprint)

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