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基于关键节点识别的社交网络舆情控制策略研究

崔雪莲 董海涛

计算机工程与应用2024,Vol.60Issue(20):262-273,12.
计算机工程与应用2024,Vol.60Issue(20):262-273,12.DOI:10.3778/j.issn.1002-8331.2310-0208

基于关键节点识别的社交网络舆情控制策略研究

Research on Social Network Public Opinion Control Strategy Based on Key Node Identification

崔雪莲 1董海涛1

作者信息

  • 1. 山东科技大学 经济管理学院,山东 青岛 266590
  • 折叠

摘要

Abstract

Effective identification of key nodes in social networks plays an important role in the control and guidance of public opinion.Aiming at the problem of social network public opinion dissemination,a control method based on key node identification is proposed.Firstly,a key node identification method based on dual index Shannon entropy is designed.Considering the importance of nodes in the global network and local network topology,the intermediate number and struc-tural hole constraint coefficient index are used as the information function to construct the node distribution probability,and then the node information entropy is calculated to identify the key nodes in the public opinion dissemination according to the size of the information entropy.Secondly,the effectiveness of the key node identification method is verified through simulation experiments,and the role of the identified key nodes in the public opinion communication is analyzed based on the SIR model.Finally,the control strategy is given.The experimental results show that this method can effectively identify the"bridge"node in the network except the network center node.In the public opinion propagation simulation,the speed and range of public opinion propagation are significantly reduced after adding the control bridge node,and the public opinion control effect is optimal when the number of key nodes is within the range of 2%~3%,and the marginal utility beyond this range is significantly reduced.

关键词

社交网络/舆情传播/关键节点/信息熵

Key words

social networks/public opinion dissemination/key nodes/Shannon entropy

分类

信息技术与安全科学

引用本文复制引用

崔雪莲,董海涛..基于关键节点识别的社交网络舆情控制策略研究[J].计算机工程与应用,2024,60(20):262-273,12.

基金项目

山东省社会科学规划研究项目(22DGLJ26) (22DGLJ26)

山东省自然科学基金(ZR2019BG011). (ZR2019BG011)

计算机工程与应用

OA北大核心CSTPCD

1002-8331

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