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Local preferential attachment model for hierarchical networks

Author

Listed:
  • Wang, Li-Na
  • Guo, Jin-Li
  • Yang, Han-Xin
  • Zhou, Tao

Abstract

In real-life networks, incomers may only connect to a few others in a local area for their limited information, and individuals in a local area are likely to have close relations. Accordingly, we propose a local preferential attachment model. Here, a local-area-network stands for a node and all its neighbors, and the new nodes perform nonlinear preferential attachment, π(ki)∝kiα, in local areas. The stable degree distribution and clustering-degree correlations are analytically obtained. With the increasing of α, the clustering coefficient increases, while assortativity decreases from positive to negative. In addition, by adjusting the parameter α, the model can generate different kinds of degree distribution, from exponential to power-law. The hierarchical organization, independent of α, is the most significant character of this model.

Suggested Citation

  • Wang, Li-Na & Guo, Jin-Li & Yang, Han-Xin & Zhou, Tao, 2009. "Local preferential attachment model for hierarchical networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1713-1720.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:8:p:1713-1720
    DOI: 10.1016/j.physa.2008.12.028
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    Citations

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    Cited by:

    1. , David, 2016. "The formation of networks with local spillovers and limited observability," Theoretical Economics, Econometric Society, vol. 11(3), September.
    2. Yang, Xu-Hua & Lou, Shun-Li & Chen, Guang & Chen, Sheng-Yong & Huang, Wei, 2013. "Scale-free networks via attaching to random neighbors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3531-3536.
    3. Wen, Guanghui & Duan, Zhisheng & Chen, Guanrong & Geng, Xianmin, 2011. "A weighted local-world evolving network model with aging nodes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 4012-4026.

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