An Opinion Evolution Model Based on Heterogeneous Benefit with Malicious Nodes Added

被引:0
|
作者
Zhao, Junwei [1 ]
Chen, Xi [1 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
GAME;
D O I
10.1155/2021/6642698
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Individuals with different levels of education have substantial differences in their willingness to communicate with malicious nodes in a group; thus, the results of evolution of opinions tend to differ significantly. In this study, malicious nodes, driven by the benefits of a game, were added to groups of individuals with different levels of education, and a theoretical model of the game theory of group opinions that introduces malicious nodes was established. The influence of the proportion of malicious node spreading messages, the extent of tampering when malicious nodes spread messages, and the distribution of education levels in the group on the evolution of group opinions were considered. It was found that the rate of evolution of group opinions declined in groups with higher average education levels. The results of this study can be used to explain the phenomenon of fewer knowledge exchange behaviors in communities with high education levels, as is found in actual sociology. The reason is that highly educated individuals are more affected by distorted news when communicating. Therefore, the loss of communication with malicious nodes is greater, resulting in lower vigilance and willingness to communicate.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Malicious Nodes Identification for Complex Network Based on Local Views
    20154101368015
    Vernize, Grazielle (gvernize@inf.ufpr.br), 1600, Oxford University Press (58):
  • [22] Malicious Nodes Identification for Complex Network Based on Local Views
    Vernize, Grazielle
    Pires Guedes, Andre Luiz
    Pessoa Albini, Luiz Carlos
    COMPUTER JOURNAL, 2015, 58 (10): : 2476 - 2491
  • [23] Simulation of Malicious Nodes Detection Based on Machine Learing for WSN
    Zou, Kuancheng
    Ouyang, Yuanling
    Niu, Chuncheng
    Zou, Yi
    INFORMATION COMPUTING AND APPLICATIONS, PT 1, 2012, 307 : 492 - +
  • [24] Trust Based Certificate Authority for Detection of Malicious Nodes in MANET
    Manoj, V.
    Raghavendiran, N.
    Aaqib, M.
    Vijayan, R.
    GLOBAL TRENDS IN COMPUTING AND COMMUNICATION SYSTEMS, PT 1, 2012, 269 : 392 - 401
  • [25] Complex Network Evolution Model Based on Microscopic Characteristic of Nodes
    Wang, Yong
    Cui, Jiahe
    Zhang, Tao
    Yang, Jing
    Zhang, Jianpei
    2018 IEEE 18TH INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY AND SECURITY COMPANION (QRS-C), 2018, : 388 - 393
  • [26] Malicious code detection based on heterogeneous information network
    Liu Y.
    Hou Y.
    Yan H.
    Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 2022, 48 (02): : 258 - 265
  • [27] Lightweight and Secure Data Transmission Scheme Against Malicious Nodes in Heterogeneous Wireless Sensor Networks
    Wang, Na
    Zhang, Shancheng
    Zhang, Zheng
    Qiao, Jiawen
    Fu, Junsong
    Liu, Jianwei
    Bhargava, Bharat K.
    IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2023, 18 : 4652 - 4667
  • [28] HANDOM: Heterogeneous Attention Network Model for Malicious Domain Detection
    Wang, Qing
    Dong, Cong
    Jian, Shijie
    Du, Dan
    Lu, Zhigang
    Qi, Yinhao
    Han, Dongxu
    Ma, Xiaobo
    Wang, Fei
    Liu, Yuling
    COMPUTERS & SECURITY, 2023, 125
  • [29] Efficiency and stability in the connections model with heterogeneous nodes *
    Olaizola, Norma
    Valenciano, Federico
    JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION, 2021, 189 : 490 - 503
  • [30] Evolution model of NIMBY opinion based on public perception and governmental guidance
    Wu X.
    Liu X.
    Zhou J.
    Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2019, 39 (11): : 2865 - 2879