Multi-Information Hybrid Network Spreading Model Based on Competition Consciousness

被引:0
作者
Wang, Yaxi [1 ]
Wang, Xuyang [1 ]
Yue, Nianxi [2 ]
机构
[1] Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Peoples R China
[2] Lanzhou Univ Technol, Sch Energy & Power Engn, Lanzhou 730050, Peoples R China
关键词
Social networking (online); Complex networks; Overlay networks; Licenses; Infectious diseases; Epidemics; Blogs; competition awareness; hybrid networks; information dissemination; VARIABLE CHAOTIC SYSTEMS; UNKNOWN-PARAMETERS; COMPLEX; SYNCHRONIZATION; IMMUNIZATION;
D O I
10.1109/ACCESS.2021.3057636
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In fact, information is not transmitted in a single message, but rather multiple messages are transmitted simultaneously and interact with each other as they are transmitted. Based on this phenomenon, a multi-information overlay network model that differs from the traditional network structure is first constructed on the basis of two classical network models, BA scale-free and WS Small World. When multiple messages are transmitted simultaneously, the competitive nature of the message affects the transmission process to some extent, and therefore a sense of competition for the message is introduced into the classical SIS model of infectious disease. Simulation experiments have shown that a sense of competition enhances or inhibits the spread of information to varying degrees, and that information with a high sense of competition has a greater scale of spread, in line with the real-life "Matthew effect". In addition, the sense of competition also accelerates the spread of information. Therefore, it is possible to inhibit the spread of negative information by controlling the sense of competition, so as to achieve timely warning and control of negative information.
引用
收藏
页码:31504 / 31512
页数:9
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  • [31] Topology evolution model for wireless multi-hop network based on socially inspired mechanism
    Luo, Xiaojuan
    Hu, Yuhen
    Zhu, Yu
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2014, 416 : 639 - 650
  • [32] Multi-layer network community detection model based on attributes and social interaction intensity
    Li, Xiaoming
    Xu, Guagquan
    Jiao, Litao
    Zhou, Yinan
    Yu, Wei
    [J]. COMPUTERS & ELECTRICAL ENGINEERING, 2019, 77 : 300 - 313
  • [33] Routing algorithm based on triangular fuzzy layer model and multi-layer clustering for opportunistic network
    Li, Zhuoyang
    Chen, Zhigang
    Wu, Jia
    Liu, Kanghuai
    [J]. IET COMMUNICATIONS, 2020, 14 (17) : 2905 - 2914
  • [34] Multi-message topic dissemination probabilistic model with memory attenuation based on Social-Messages Network
    Yang, Ruiqi
    Han, Dingding
    Qian, Jianghai
    [J]. INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2019, 30 (07):
  • [35] Agent-based multi-edge network simulation model for knowledge diffusion through board interlocks
    Sankar, C. Prem
    Thumba, Drisya Alex
    Ramamohan, T. R.
    Chandra, S. S. Vinod
    Kumar, K. Satheesh
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2020, 141
  • [36] DeepNetBim: deep learning model for predicting HLA-epitope interactions based on network analysis by harnessing binding and immunogenicity information
    Yang, Xiaoyun
    Zhao, Liyuan
    Wei, Fang
    Li, Jing
    [J]. BMC BIOINFORMATICS, 2021, 22 (01)