基于超网络的新冠肺炎舆情关键节点识别研究

Research on the Identification of Key Nodes in Public Opinion of COVID-19 Based on Super Network

所谓新冠肺炎舆情,就是互联网上广大网友对新冠肺炎疫情这一突发的公共卫生事件所表达的看法的总和。由于消息在传播过程中往往出现“信息失真”问题,这使得原来可以促进疫情防控的积极网络舆情可能随时转化为对疫情防控等工作产生消极影响。因此为实现相关部门精准干预并掌控新冠肺炎舆情传播朝着正向发展的目的,识别新冠肺炎舆情的关键节点是至关重要的。将超网络的理论基础运用到新冠肺炎舆情传播中的各个子网建模,应用Matlab、python仿真分析确定新冠肺炎舆情中的关键节点。

The so-called public opinion on COVID-19 is the sum of the opinions expressed by the majority of netizens on the Internet on the sudden public health event of public opinion on COVID-19.Due to the problem of"information distortion"in the pro⁃cess of news dissemination,the positive public opinion that can promote epidemic prevention and control online may be transformed into a negative impact on epidemic prevention and control at any time.Therefore,in order to achieve the accurate intervention by rel⁃evant departments and control the public opinion spread of COVID-19 towards positive development,it is crucial to identify the key nodes of public opinion of COVID-19.The theoretical basis of the super network is applied to the modeling of each sub-network in the spread of public opinion of COVID-19,Matlab and python simulation analysis are used to determine the key nodes in the public opinion of COVID-19.