Co-evolution of the brand effect and competitiveness in evolving networks

被引:0
|
作者
郭进利 [1 ]
机构
[1] Business School,University of Shanghai for Science and Technology
基金
中国国家自然科学基金;
关键词
complex network; weighted network; scale-free network; competitive network;
D O I
暂无
中图分类号
O157.5 [图论];
学科分类号
070104 ;
摘要
The principle that ‘the brand effect is attractive’ underlies the preferential attachment. Here we show that the brand effect is just one dimension of attractiveness. Another dimension is competitiveness. We firstly introduce a general framework that allows us to investigate the competitive aspect of real networks, instead of simply preferring popular nodes. Our model accurately describes the evolution of social and technological networks. The phenomenon that more competitive nodes become richer can help us to understand the evolution of many competitive systems in nature and society. In general,the paper provides an explicit analytical expression of degree distributions of the network. In particular, the model yields a nontrivial time evolution of nodes’ properties and the scale-free behavior with exponents depending on the microscopic parameters characterizing the competition rules. Secondly, through theoretical analyses and numerical simulations, we reveal that our model has not only the universality for the homogeneous weighted network, but also the character for the heterogeneous weighted network. Thirdly, we also develop a model based on the profit-driven mechanism. It can better describe the observed phenomenon in enterprise cooperation networks. We show that the standard preferential attachment,the growing random graph, the initial attractiveness model, the fitness model, and weighted networks can all be seen as degenerate cases of our model.
引用
收藏
页码:234 / 241
页数:8
相关论文
共 50 条
  • [1] Co-evolution of the brand effect and competitiveness in evolving networks
    Guo Jin-Li
    [J]. CHINESE PHYSICS B, 2014, 23 (07)
  • [2] The Co-Evolution Analysis of Industrial Clusters and Regional Brand
    Zhao, Huiyue
    Yang, Xintong
    Guo, Xiaoli
    [J]. 2013 INTERNATIONAL CONFERENCE ON MANAGEMENT (ICM 2013), 2013, : 1429 - 1433
  • [3] Modular co-evolution of metabolic networks
    Jing Zhao
    Guo-Hui Ding
    Lin Tao
    Hong Yu
    Zhong-Hao Yu
    Jian-Hua Luo
    Zhi-Wei Cao
    Yi-Xue Li
    [J]. BMC Bioinformatics, 8
  • [4] Co-evolution of Social and Affiliation Networks
    Zheleva, Elena
    Sharara, Hossam
    Getoor, Lise
    [J]. KDD-09: 15TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2009, : 1007 - 1015
  • [5] Modular co-evolution of metabolic networks
    Zhao, Jing
    Ding, Guo-Hui
    Tao, Lin
    Yu, Hong
    Yu, Zhong-Hao
    Luo, Jian-Hua
    Cao, Zhi-Wei
    Li, Yi-Xue
    [J]. BMC BIOINFORMATICS, 2007, 8 (1)
  • [6] Co-evolution and co-adaptation in protein networks
    Juan, David
    Pazos, Florencio
    Valencia, Alfonso
    [J]. FEBS LETTERS, 2008, 582 (08) : 1225 - 1230
  • [7] The Co-Evolution Model for Social Network Evolving and Opinion Migration
    Gu, Yupeng
    Sun, Yizhou
    Gao, Jianxi
    [J]. KDD'17: PROCEEDINGS OF THE 23RD ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2017, : 175 - 184
  • [8] Rapidly Evolving MicroRNAs Retain Their Targets by a Co-Evolution Mechanism
    Ramaiah, Madhuvanthi
    Shum, Eleen Y.
    Wilkinson, Miles F.
    [J]. FASEB JOURNAL, 2012, 26
  • [9] Co-Evolution with Social Networks: Deception Is Protection
    Orman, Hilarie
    [J]. IEEE INTERNET COMPUTING, 2014, 18 (03) : 90 - 94
  • [10] Co-evolution of Firms, Industries and Networks in Space
    Ter Wal, Anne L. J.
    Boschma, Ron
    [J]. REGIONAL STUDIES, 2011, 45 (07) : 919 - 933