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Emergence of scaling and assortative mixing through altruism

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  • Li, Ping
  • Zhang, Jie
  • Small, Michael

Abstract

Many social networks, apart from displaying scale-free characteristics observed in some instances, possess another remarkable feature that distinguishes them from those that appear in biological and technological context—assortativity. However, little or no attention has been payed to the mechanism of assortativity in modeling these networks. Inspired by individuals’ altruistic behavior in sociology, we develop a model with a different growth mechanism called “altruistic attachment”, which can reproduce not only the power law degree distribution but degree correlations. We study in detail the statistical properties of our network model, which we also demonstrate striking differences with the BA model, and can portray real social networks more precisely.

Suggested Citation

  • Li, Ping & Zhang, Jie & Small, Michael, 2011. "Emergence of scaling and assortative mixing through altruism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2192-2197.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:11:p:2192-2197
    DOI: 10.1016/j.physa.2011.02.018
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    Cited by:

    1. Mohd-Zaid, Fairul & Kabban, Christine M. Schubert & Deckro, Richard F. & White, Edward D., 2017. "Parameter specification for the degree distribution of simulated Barabási–Albert graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 141-152.
    2. Moore, Jack Murdoch & Small, Michael & Yan, Gang, 2021. "Inclusivity enhances robustness and efficiency of social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    3. Zhang, Linjun & Small, Michael & Judd, Kevin, 2015. "Exactly scale-free scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 182-197.
    4. Zhang, Lan & Huang, Changwei, 2023. "Preferential selection to promote cooperation on degree–degree correlation networks in spatial snowdrift games," Applied Mathematics and Computation, Elsevier, vol. 454(C).

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