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The Analysis of the Power Law Feature in Complex Networks

Consensus about the universality of the power law feature in complex networks is experiencing widespread challenges. In this paper, we propose a generic theoretical framework in order to examine the power law property. First, we study a class of birth-and-death networks that are more common than BA...

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Autores principales: Zhang, Xiaojun, He, Zheng, Zhang, Liwei, Rayman-Bacchus, Lez, Shen, Shuhui, Xiao, Yue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689370/
https://www.ncbi.nlm.nih.gov/pubmed/36359650
http://dx.doi.org/10.3390/e24111561
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author Zhang, Xiaojun
He, Zheng
Zhang, Liwei
Rayman-Bacchus, Lez
Shen, Shuhui
Xiao, Yue
author_facet Zhang, Xiaojun
He, Zheng
Zhang, Liwei
Rayman-Bacchus, Lez
Shen, Shuhui
Xiao, Yue
author_sort Zhang, Xiaojun
collection PubMed
description Consensus about the universality of the power law feature in complex networks is experiencing widespread challenges. In this paper, we propose a generic theoretical framework in order to examine the power law property. First, we study a class of birth-and-death networks that are more common than BA networks in the real world, and then we calculate their degree distributions; the results show that the tails of their degree distributions exhibit a distinct power law feature. Second, we suggest that in the real world two important factors—network size and node disappearance probability—will affect the analysis of power law characteristics in observation networks. Finally, we suggest that an effective way of detecting the power law property is to observe the asymptotic (limiting) behavior of the degree distribution within its effective intervals.
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spelling pubmed-96893702022-11-25 The Analysis of the Power Law Feature in Complex Networks Zhang, Xiaojun He, Zheng Zhang, Liwei Rayman-Bacchus, Lez Shen, Shuhui Xiao, Yue Entropy (Basel) Article Consensus about the universality of the power law feature in complex networks is experiencing widespread challenges. In this paper, we propose a generic theoretical framework in order to examine the power law property. First, we study a class of birth-and-death networks that are more common than BA networks in the real world, and then we calculate their degree distributions; the results show that the tails of their degree distributions exhibit a distinct power law feature. Second, we suggest that in the real world two important factors—network size and node disappearance probability—will affect the analysis of power law characteristics in observation networks. Finally, we suggest that an effective way of detecting the power law property is to observe the asymptotic (limiting) behavior of the degree distribution within its effective intervals. MDPI 2022-10-29 /pmc/articles/PMC9689370/ /pubmed/36359650 http://dx.doi.org/10.3390/e24111561 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Xiaojun
He, Zheng
Zhang, Liwei
Rayman-Bacchus, Lez
Shen, Shuhui
Xiao, Yue
The Analysis of the Power Law Feature in Complex Networks
title The Analysis of the Power Law Feature in Complex Networks
title_full The Analysis of the Power Law Feature in Complex Networks
title_fullStr The Analysis of the Power Law Feature in Complex Networks
title_full_unstemmed The Analysis of the Power Law Feature in Complex Networks
title_short The Analysis of the Power Law Feature in Complex Networks
title_sort analysis of the power law feature in complex networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689370/
https://www.ncbi.nlm.nih.gov/pubmed/36359650
http://dx.doi.org/10.3390/e24111561
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