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Growing scale-free small-world networks with tunable assortative coefficient

Author

Listed:
  • Guo, Qiang
  • Zhou, Tao
  • Liu, Jian-Guo
  • Bai, Wen-Jie
  • Wang, Bing-Hong
  • Zhao, Ming

Abstract

In this paper, we propose a simple rule that generates scale-free small-world networks with tunable assortative coefficient. These networks are constructed by two-stage adding process for each new node. The model can reproduce scale-free degree distributions and small-world effect. The simulation results are consistent with the theoretical predictions approximately. Interestingly, we obtain the nontrivial clustering coefficient C and tunable degree assortativity r by adjusting the parameter: the preferential exponent β. The model can unify the characterization of both assortative and disassortative networks.

Suggested Citation

  • Guo, Qiang & Zhou, Tao & Liu, Jian-Guo & Bai, Wen-Jie & Wang, Bing-Hong & Zhao, Ming, 2006. "Growing scale-free small-world networks with tunable assortative coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 814-822.
    • Handle: RePEc:eee:phsmap:v:371:y:2006:i:2:p:814-822
    DOI: 10.1016/j.physa.2006.03.055
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    Citations

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    Cited by:

    1. Thomas Chesney, 2017. "The Cascade Capacity Predicts Individuals to Seed for Diffusion Through Social Networks," Systems Research and Behavioral Science, Wiley Blackwell, vol. 34(1), pages 51-61, January.
    2. Junuo Zhou & Lin Yang, 2022. "Network-Based Research on Organizational Resilience in Wuhan Thunder God Mountain Hospital Project during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    3. Reppas, Andreas I. & Spiliotis, Konstantinos & Siettos, Constantinos I., 2015. "Tuning the average path length of complex networks and its influence to the emergent dynamics of the majority-rule model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 109(C), pages 186-196.
    4. Hazem Krichene & Mhamed-Ali El-Aroui, 2018. "Agent-Based Simulation and Microstructure Modeling of Immature Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 493-511, March.
    5. Hazem Krichene & Mhamed-Ali El-Aroui, 2018. "Artificial stock markets with different maturity levels: simulation of information asymmetry and herd behavior using agent-based and network models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 511-535, October.
    6. Leary, C.C. & Schwehm, M. & Eichner, M. & Duerr, H.P., 2007. "Tuning degree distributions: Departing from scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 731-738.
    7. Wen, Xing-Zhang & Zheng, Yue & Du, Wen-Li & Ren, Zhuo-Ming, 2023. "Regulating clustering and assortativity affects node centrality in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).

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