Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics

Abstract

With the development of information technology, the Internet has become an important channel of public opinion for expressing public interests, emotion, and ideas. Public emergency usually spreads via network. Due to the temporal and spatial flexibility and the information amplification of network, the opinions from different regions and background are easy to be represented as network public opinion, and have important impact on social and economic life. Thus, studying the formation mechanism of network public opinion has important theoretical and practical significance. Taking the formation process of network public opinion under emergencies as the research object, this paper first identifies the key factors influencing the formation of network public opinion, namely the internal characteristics (include individual education level, individual stubbornness, individual initial opinion, and so on) and external information of individuals (include external information intensity). Second, information intensity is introduced to describe the influence of external information feature on the formation of network public opinion. Individual education level, individual stubbornness, and individual initial opinion are analyzed to describe the influence of individual internal factors on the formation, and then its model is constructed. Through the simulation experiments, this paper analyzes the influence of external information intensity, individual education level, individual stubbornness, individual initial opinion, and other factors on the formation of network public opinion. The simulation results show that: (1) the greater intensity of public emergency reporting causes the easier formation of network public opinion; (2) the higher individual education level leads to the shorter time for completing the final formation and stable state of online public opinions, and after the formation of online public opinions, the opinion of the event is mainly neutral; (3) the greater individual's stubbornness makes the shorter formation time of online public opinion. When online public opinion reaches a stable state, the neutral opinion group dominates and firmly controls the development trend of public opinion; (4) the difference of opinions among individuals is the most important factor affecting the formation of network public opinion. Finally, the rationality and validity of the proposed model are verified by a real case. Compared with previous studies on the formation mechanism of network public opinion, this paper divides the formation process of network public opinion into three stages: individual information perception, individual decision

Interoperability of Multimedia Network Public Opinion Knowledge Base Group Based on Multisource Text Mining

“…How to interoperate between heterogeneous knowledge bases has become a main problem in the current information management department that needs to be solved by domestic and foreign scholars. It has become one of the main problems that domestic and foreign scholars need to solve that the relevant government departments provide crossplatform, cross-system knowledge association, analysis, and text mining [1,2]. e interoperation of different types of public opinion knowledge base groups has become the main means to complete the crossover and integration of multimedia public opinion data information under big data [3,4], and it has also become an effective means for the acquisition, preservation, and use of big data information for multimedia network public opinion [5].…”

Online Fake News Opinion Spread and Belief Change: A Systematic Review

“…This was demonstrated in [59] for the climate change topic and the topic of public opinion about police funding [64] at around the time of the murder of George 7 Human Behavior and Emerging Technologies Floyd at the hands of law enforcement in the United States [155]. It was also seen that the level of a person's stubbornness was shown to be inversely correlated to the probability of belief change [55]. The hypothesized correlation between emotional arousal and polarization was confirmed.…”

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

“…Through the literature review on the influencing factors and propagation rules of online public opinion, it was found that the research on the influencing factors of new coronavirus online public opinion is mostly concentrated in computer science and other fields. These studies usually analyze online public opinions from the perspective of data modeling [ 25 , 26 , 27 ]. At present, there is a lack of systematic identification and risk interaction research on risk factors of COVID-19, and the research on risk transmission mechanism of online public opinion of COVID-19 is relatively insufficient.…”