基于SIsnoR的网络舆情传播动力学建模与仿真  

The Modelling and Simulation of Internet Public Opinion Dissemination Dynamics Based on SIsnoR

在线阅读下载全文

作  者:张志霞[1] 苏丙康 ZHANG Zhixia;SU Bingkang(School of Management,Xi’an University of Architecture and Technology,Xi’an 710055,China)

机构地区:[1]西安建筑科技大学管理学院,西安710055

出  处:《情报工程》2022年第5期74-85,共12页Technology Intelligence Engineering

基  金:陕西省自然科学基金“基于用户画像的社交媒体耦合网络舆情演化及预警机制研究”(2022JM-416)。

摘  要:[目的/意义]随着智能化时代网络空间信息辐射方式的改变以及政府、媒体与民众等的大量介入,网络舆情社会治理难度日益加大,如何有效提升突发舆情事件的应对和处理能力,研究舆情主体的传播动力学特性就凸显其重要意义。[方法/过程]基于经典SIR模型,突破现有单一主体作用或单一传播群体分化现状,构建了由政府、媒体和网民多主体作用的新型SIsnoR模型,并以2021年“东北限电事件”为例研究了互联网环境下舆情传播的影响机理。[结果/结论]基于SIsnoR的网络舆情传播动力学模型能够很好地刻画多主体作用下的网络舆情传播特征,为政府和媒体对于新时代的网络舆情协同治理提供理论依据。[Purpose/Significance]With the change of the radiation mode of cyberspace information in the intelligent era and the massive involvement of the government,media and the public,the social governance of internet public opinion has become increasingly diffcult.How to effectively improve the response and handling capacity of public opinion emergencies,and study the propagation dynamics of public opinion subjects has become increasingly important.[Methods/Processes]Based on the classic SIR model,a new SIsnoR model with multiple roles of government,media and Internet users has been built by breaking through the existing status quo of single subject role or single communication group differentiation,and the impact mechanism of public opinion communication under the Internet environment has been studied by taking the“Northeast Power Cut Event”in 2021 as an example.[Results/Conclusions]The simulation results show that the dynamic model of internet public opinion communication based on SIsno Rcan well describe the characteristics of internet public opinion communication under the multi-agent action,and provide a theoretical basis for the government and the media for the collaborative governance of internet public opinion in the new era.

关 键 词:突发事件 网络舆情 多主体 SIsnoR模型 传播动力学 建模仿真 

分 类 号:G35[文化科学—情报学] TP391[自动化与计算机技术—计算机应用技术]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象