New media platform's understanding of Chinese social workers' anti-epidemic actions: an analysis of network public opinion based on COVID-19

The relationship between young college students' recognition of national COVID-19 crisis governance capabilities and the improvement of national identity: the mediating role of online participation in public health critical events

Background

Improving the young college students' national identity is crucial for ensuring social stability and fostering development during public health critical events such as COVID-19. Young college students' recognition of national COVID-19 crisis governance capabilities can influence their national identity, and online participation in public health criticalevents may serve as a crucial role in shaping this intricate relationship. To investigate this possibility, the present study established an intermediary model to examine the impact of online participation in public health critical events on young college students' recognition of national COVID-19 crisis governance capabilities and improvement of national identity.

Methods

This cross-sectional survey study employed a convenience sampling method to investigate a total of 3041 young college students in China. The correlations between study variables were analyzed using Spearman's rank correlation. The mediation model was established using PROCESS Model 4 with 5000 bootstrap samples in SPSS. The bias-corrected bootstrap method provided statistical efficacy and identification interval estimation.

Results

Young college students' recognition of national COVID-19 crisis governance capabilities (r=0.729, P<0.001) and online participation in public health critical events (r=0.609, P<0.001) were positively correlated with improvement of their national identity. The relationship between these two factors was partially mediated by online participation in public health critical events (Indirect effect estimate=0.196, P<0.001).

Conclusion

Online participation in public health critical events played a mediating role in the association between college students' recognition of national COVID-19 crisis governance capabilities and the improvement of national identity. Our findings provide a novel intervention strategy for improving college students' national identity, which is to encourage their online participation in public health critical events.

Using Grounded Theory to Identify Online Public Opinion in China to Improve Risk Management-The Case of COVID-19

BACKGROUND

During the outbreak of COVID-19, online public opinion related to the epidemic was rapidly generated and developed rapidly. If some online public opinions cannot be effectively responded to and guided, it will bring risks to social order. The government should understand how to use information on social media to grasp public demands, provide useful information in a timely manner and take countermeasures. Studying the formation mechanism of online public opinion during the outbreak can help the government make scientific decisions and improve risk management capabilities.

METHODS

The research selects the public opinion information of online platforms represented by WeChat, online communities, Sina Weibo and search engines, involving 75 relevant texts (1 January to 31 March 2022). According to the grounded theory method, using the QSR NVivo12 qualitative research software, the collected network texts were successively researched using open coding, axial coding and theoretical coding.

RESULTS

The structure of online public opinion during the COVID-19 epidemic was obtained. The operation mechanism of the online public opinion system about COVID-19 was mainly affected by the interaction of online public opinion objects, online public opinion subjects, online public opinion intermediaries and government forces. It was based on social facts and citizens' appeals as the starting point, subject behaviors and prevention and control measures as the focus, government's governance as macro-control and citizens' evaluation as the guide.

CONCLUSIONS

Scientific analysis of online public opinion is an important tool to identify and manage risks and improve the quality of government activities. Online public opinion has the function of assisting government decision-making, and the government can identify the important information reflected in it, especially the mainstream public opinion, as a reference for decision-making. By taking effective measures and properly responding to citizens' reasonable demands, the government can prevent social risks and avoid new negative public opinions. Contributions: According to the characteristics of the basic model of online public opinion, this study provides risk mitigation suggestions for Chinese public sectors to use online public opinion, optimize epidemic prevention policies and formulate strategic measures.

How local outbreak of COVID-19 affect the risk of internet public opinion: A Chinese social media case study

Motivated by the realistic demand of controlling the Internet public opinion risk caused by the local outbreak of COVID-19, this paper creatively proposes a COVID-19 local outbreak Internet public opinion risk grading research framework. The SMAA-FAHPSort II method combining Analytic Hierarchy Process Sort II (AHPSort II) method with Stochastic Multicriteria Acceptability Analysis (SMAA-2) method is introduced into this framework, to evaluate the Internet public opinion risk level of social media during the local outbreak of COVID-19. In addition, this framework is applied to a case of Internet public opinion risk evaluation on Microblog platform of China. According to the number of new cases per day in mainland China, this paper divides the period from May 7, 2020 to September 3, 2021 into seven stages. A total of more than 10,000 Microblog hot topics were collected, after screening and preprocessing, 5422 related topics are remained to help complete the Internet public opinion risk evaluation. The case study analysis results show that the number of days classified as moderate risk and above has reached more than 280. This proves that the local outbreak of COVID-19 will indeed increase the risk of Internet public opinion, and correlation analysis confirms that the level of public opinion risk is positively correlated with the severity of the epidemic in the real world. Furthermore, the effectiveness and advantages of the proposed method are verified by comparative analysis and sensitivity analysis. Finally, some effective public opinion management suggestions have been put forward. This paper can provide reference for the government to formulate or improve relevant strategies, and also has great significance for reducing the risk of Internet public opinion in social media.

Analysis on the Impact and Management of Political Education of College Students in the Micro Era Environment

With the rapid development of modern society and the popularization of information equipment, information transmission has broken the time and space constraints, and political education (PE) can be carried out anytime and anywhere. Micro media is the product of the rapid development of science and technology, which has brought us into a new "micro era." The research on the "micro era" has been the focus of academic attention in recent years. Especially with the popularization of micro media, its influence on people is becoming deeper, making more scholars in academic circles devote themselves to the "micro era" under study. However, while micro media is widely used by college students (CS), it also brings opportunities and challenges. Therefore, it is particularly important to clarify the opportunities and challenges faced by CS' PE under the background of the "micro era" and put forward practical countermeasures. Starting from the actual situation of PE communication in the micro era, this study analyzes the opportunities and challenges brought by the "micro era" to PE of CS through a questionnaire survey. Then, the effective strategies to improve the PE of CS are explored, in order to improve the ideological and political level of CS in the micro era.

Application of edge computing combined with deep learning model in the dynamic evolution of network public opinion in emergencies

The aim is to clarify the evolution mechanism of Network Public Opinion (NPO) in public emergencies. This work makes up for the insufficient semantic understanding in NPO-oriented emotion analysis and tries to maintain social harmony and stability. The combination of the Edge Computing (EC) and Deep Learning (DL) model is applied to the NPO-oriented Emotion Recognition Model (ERM). Firstly, the NPO on public emergencies is introduced. Secondly, three types of NPO emergencies are selected as research cases. An emotional rule system is established based on the One-Class Classification (OCC) model as emotional standards. The word embedding representation method represents the preprocessed Weibo text data. Convolutional Neural Network (CNN) is used as the classifier. The NPO-oriented ERM is implemented on CNN and verified through comparative experiments after the CNN's hyperparameters are adjusted. The research results show that the text annotation of the NPO based on OCC emotion rules can obtain better recognition performance. Additionally, the recognition effect of the improved CNN is significantly higher than the Support Vector Machine (SVM) in traditional Machine Learning (ML). This work realizes the technological innovation of automatic emotion recognition of NPO groups and provides a basis for the relevant government agencies to handle the NPO in public emergencies scientifically.

Modeling and simulation of microblog-based public health emergency-associated public opinion communication

With the advent of the era of “we media,” many people's opinions have become easily accessible. Public health emergencies have always been an important aspect of public opinion exchange and emotional communication. In view of this sudden group panic, public opinion cannot be effectively monitored, controlled or guided. This makes it easy to amplify the beliefs and irrationality of social emotions, that threaten social security and stability. Considering the important role of opinion leaders in micro-blogs and users’ interest in micro-blog information, a SIR model of public opinion propagation is constructed based on the novel coronavirus pneumonia model and micro-blog's public health emergencies information. The parameters of the model are calculated by combining the actual crawl data from the novel coronavirus pneumonia epidemic period, and the trends in the evolution of public opinion are simulated by MATLAB. The simulation results are consistent with the actual development of public opinion dissemination, which shows the effectiveness of the model. These research findings can help the government understand the principles that guide the propagation of public opinion and advise an appropriate time to control and correctly guide public opinion.