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Volume 13, Issue 2
A Scale-Free Network Evolution Model Based on the Growth Characteristics of Social Networks

Qi Yang and Yulong Shi

J. Info. Comput. Sci. , 13 (2018), pp. 125-130.

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  • Abstract
In this paper, based on the classic BA scale-free network model, we proposed a new evolution model that gives a more realistic description of the people’s behavior on social networks. In the process of growth, there are local preferential attachment mechanisms and random attachment or removal between the old and new edges. We proved that the extended model follows the power-law distribution and the power exponent is between 2 and 3, which provides a theoretical support for analyzing the similar social network. Compared with the classic BA model, the extended model has a smaller average path length and a larger clustering coefficient, which is more consistent with the real social network.
  • Keywords

BA scale-free network, social network, local preferential attachment, random attachment

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COPYRIGHT: © Global Science Press

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@Article{JICS-13-125, author = {Qi Yang and Yulong Shi}, title = {A Scale-Free Network Evolution Model Based on the Growth Characteristics of Social Networks}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {13}, number = {2}, pages = {125--130}, abstract = {In this paper, based on the classic BA scale-free network model, we proposed a new evolution model that gives a more realistic description of the people’s behavior on social networks. In the process of growth, there are local preferential attachment mechanisms and random attachment or removal between the old and new edges. We proved that the extended model follows the power-law distribution and the power exponent is between 2 and 3, which provides a theoretical support for analyzing the similar social network. Compared with the classic BA model, the extended model has a smaller average path length and a larger clustering coefficient, which is more consistent with the real social network. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22454.html} }
TY - JOUR T1 - A Scale-Free Network Evolution Model Based on the Growth Characteristics of Social Networks AU - Qi Yang and Yulong Shi JO - Journal of Information and Computing Science VL - 2 SP - 125 EP - 130 PY - 2024 DA - 2024/01 SN - 13 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22454.html KW - BA scale-free network, social network, local preferential attachment, random attachment AB - In this paper, based on the classic BA scale-free network model, we proposed a new evolution model that gives a more realistic description of the people’s behavior on social networks. In the process of growth, there are local preferential attachment mechanisms and random attachment or removal between the old and new edges. We proved that the extended model follows the power-law distribution and the power exponent is between 2 and 3, which provides a theoretical support for analyzing the similar social network. Compared with the classic BA model, the extended model has a smaller average path length and a larger clustering coefficient, which is more consistent with the real social network.
Qi Yang and Yulong Shi. (2024). A Scale-Free Network Evolution Model Based on the Growth Characteristics of Social Networks. Journal of Information and Computing Science. 13 (2). 125-130. doi:
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