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
下载
收藏
页数:9
相关论文
共 50 条
  • [41] DEFENDING AGAINST MALICIOUS NODES USING AN SVM BASED REPUTATION SYSTEM
    Akbani, Rehan
    Korkmaz, Turgay
    Raju, G. V. S.
    2008 IEEE MILITARY COMMUNICATIONS CONFERENCE: MILCOM 2008, VOLS 1-7, 2008, : 2238 - 2244
  • [42] Blockchain-Based Trust and Authentication Model for Detecting and Isolating Malicious Nodes in Flying Ad Hoc Networks
    Qureshi, Kashif Naseer
    Nafea, Hanaa
    Tariq Javed, Ibrahim
    Zrar Ghafoor, Kayhan
    IEEE ACCESS, 2024, 12 : 95390 - 95401
  • [43] Opinion evolution model with the state of neutrality
    He, MF
    Sun, Q
    Wang, HS
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2004, 15 (06): : 767 - 774
  • [44] Malicious Blockchain Domain Detection Based on Heterogeneous Information Network
    Han, Jian
    Wang, Zhonghua
    Jiang, Songhao
    Zang, Tianning
    2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), 2022, : 2597 - 2602
  • [45] Evolutionary Multi-model Federated Learning on Malicious and Heterogeneous Data
    Shang, Chikai
    Gu, Fangqing
    Jiang, Jiaqi
    2023 23RD IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS, ICDMW 2023, 2023, : 386 - 395
  • [46] Impact of Heterogeneity on Opinion Dynamics: Heterogeneous Interaction Model
    Chen, Xi
    Wu, Zhan
    Wang, Hongwei
    Li, Wei
    COMPLEXITY, 2017,
  • [47] Event Feature Pre-training Model Based on Public Opinion Evolution
    Wang, Nan
    Tan, Shu-Ru
    Xie, Xiao-Lan
    Li, Hai-Rong
    Jiang, Jia-Hui
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2023, 14 (04) : 197 - 206
  • [48] HK-SEIR model of public opinion evolution based on communication factors
    Li, Qing
    Du, YaJun
    Li, ZhaoYan
    Hu, JinRong
    Hu, RuiLin
    Lv, BingYan
    Jia, Peng
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2021, 100
  • [49] Multimedia detection algorithm of malicious nodes in intelligent grid based on fuzzy logic
    Mingming Gao
    Yue Wu
    Jingchang Nan
    Shuyang Cui
    Multimedia Tools and Applications, 2019, 78 : 24011 - 24022
  • [50] Research on online and offline public opinion evolution model based on the theory of supernetwork
    Chi Y.
    Liu Y.
    Xitong Gongcheng Lilum yu Shijian, 2019, 1 (259-272): : 259 - 272