School of Network Communication, Zhejiang YueXiu University, Shaoxing 312000, China.
School of Media and Communication, Kwangwoon University, Seoul 01897, Republic of Korea.
J Environ Public Health. 2022 Aug 5;2022:5162840. doi: 10.1155/2022/5162840. eCollection 2022.
In the current environment where the network and the real society are intertwined, the network public view of public emergencies has involved in reality and altered the ecology of communal public views in China. A new online court of influence has been created, and it affected the trend of events. As the main type of public emergencies, public health emergencies are directly related to people's health and life insurance. Therefore, the public often pays special attention. At present, correct media guidance plays an irreplaceable and important role in calming people's hearts and stabilizing social order. If news and public view are left unchecked, it is likely to cause panic among the people. However, in reality, public view research has always been a research object that is difficult to intelligentize and quantify. Based on such a realistic background, the article conducts a research on public view of public health emergencies based on artificial intelligence data analysis. This study designs an expert system for network public view and optimizes the algorithm for the key problem: SFC deployment. Finally, the system was put into real news and public opinion research on new coronavirus epidemic prevention, and experimental tests were carried out. The experimental results have shown that in the new coronavirus incident, the nuclear leakage incident, and the epidemic prevention policy, the data obtained by the public through the Internet are 50%, 68.06%, and 64.35%, respectively. For the system function in this study, both ICSO and IPSO are far better than the optimization results of CSO and PSO. For most of the test functions, IPSO is better than ICSO's optimization results, which better fulfills the needs of the research content. This study will make an in-depth analysis of the evolution process of online public opinion on public emergencies from the macro-, meso-, and micro-perspectives, in order to analyze the dissemination methods and internal evolution mechanism of various public emergencies of online public opinion, which provides countermeasures and suggestions for the government to guide and manage network public opinion.
在网络与现实社会交织的当下环境中，网络公共突发事件舆情已经涉入现实，改变了中国公共意见的共同体生态。一个新的网络舆论法庭已经建立，并影响了事件的趋势。作为公共突发事件的主要类型，公共卫生突发事件直接关系到人民的健康和生命安全。因此，公众往往特别关注。目前，正确的媒体引导在稳定人心、稳定社会秩序方面发挥着不可替代的重要作用。如果新闻和公共舆论不受控制，很可能会引起民众恐慌。然而，在现实中，公共舆论研究一直是一个难以实现智能化和量化的研究对象。基于这样一个现实背景，本文基于人工智能数据分析对公共卫生突发事件舆情进行了研究。本研究设计了一个网络公共舆情专家系统，并对关键问题的算法进行了优化：SFC 部署。最后，将系统应用于新型冠状病毒疫情防控的新闻和公众舆论研究，并进行了实验测试。实验结果表明，在新型冠状病毒事件、核泄漏事件和防疫政策中，公众通过互联网获得的数据分别为 50%、68.06%和 64.35%。对于本研究中的系统功能，ICS0 和 IPSO 都远远优于 CSO 和 PSO 的优化结果。对于大多数测试函数，IPSO 都优于 ICS0 的优化结果，更好地满足了研究内容的需求。本研究将从宏观、中观和微观三个层面深入分析公共突发事件网络舆情的演变过程，分析网络舆情各种公共突发事件的传播方式和内在演变机制，为政府引导和管理网络舆情提供对策和建议。
