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A Study on Scale Free Social Network Evolution Model with Degree Exponent < 2

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Abstract

Inspired by real world phenomena, in this paper, the authors present a power law evolutional network model with degree exponent β < 2. Combinatorial probabilistic method is applied to the theoretical analysis of the presented model. In the proposed model, each time stamp the number of links among a newly added node and old ones follows Poisson distribution with parameter λ and selection probability p. The authors derive exact analytical relationship between the exponent of the power law β, the parameters λ and p. Simulation result is consistent with the exponent β analytical solution. Both theoretical analysis and simulation results show that the presented network evolution model has two obvious real world social network characteristics, degree exponent β < 2 and bending phenomena.

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Author information

Authors and Affiliations

  1. School of Mathematics and Computer Sciences, Dali University, Dali, 671003, China

    Zhenpeng Li

  2. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China

    Xijin Tang

  3. University of Chinese Academy of Sciences, Beijing, 100049, China

    Xijin Tang

Authors
  1. Zhenpeng Li
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  2. Xijin Tang
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Corresponding author

Correspondence to Zhenpeng Li.

Additional information

This research was supported by the National Natural Science Foundation of China under the Grant Nos. 71661001, 61473284, the Key Program of National Natural Science Foundation of China under Grant No. 71731002.

This paper was recommended for publication by Editor CHEN Jie.

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Li, Z., Tang, X. A Study on Scale Free Social Network Evolution Model with Degree Exponent < 2. J Syst Sci Complex 33, 87–99 (2020). https://doi.org/10.1007/s11424-020-8007-5

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  • DOI: https://doi.org/10.1007/s11424-020-8007-5

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