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An Adaptive Hierarchical Network Model for Studying the Structure of Economic Network

The interdependence of financial institutions is primarily responsible for creating a systemic hierarchy in the industry. In this paper, an Adaptive Hierarchical Network Model is proposed to study the problem of hierarchical relationships arising from different individuals in the economic domain. In...

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Detalles Bibliográficos
Autores principales: Yang, Xiaoteng, Wu, Zhenqiang, Javaid, Shumaila
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141125/
https://www.ncbi.nlm.nih.gov/pubmed/35626585
http://dx.doi.org/10.3390/e24050702
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author Yang, Xiaoteng
Wu, Zhenqiang
Javaid, Shumaila
author_facet Yang, Xiaoteng
Wu, Zhenqiang
Javaid, Shumaila
author_sort Yang, Xiaoteng
collection PubMed
description The interdependence of financial institutions is primarily responsible for creating a systemic hierarchy in the industry. In this paper, an Adaptive Hierarchical Network Model is proposed to study the problem of hierarchical relationships arising from different individuals in the economic domain. In the presented dynamically evolving network model, new directed edges are generated depending on the existing nodes and the hierarchical structures among the network, and these edges decay over time. When the preference of nodes in the network for higher ranks exceeds a certain threshold value, the equality state in the network becomes unstable and rank states emerge. Meanwhile, we select four real data sets for model evaluation and observe the resilience in the network hierarchy evolution and the differences formed by different patterns of hierarchy preference mechanisms, which help us better understand data science and network dynamics evolution.
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spelling pubmed-91411252022-05-28 An Adaptive Hierarchical Network Model for Studying the Structure of Economic Network Yang, Xiaoteng Wu, Zhenqiang Javaid, Shumaila Entropy (Basel) Article The interdependence of financial institutions is primarily responsible for creating a systemic hierarchy in the industry. In this paper, an Adaptive Hierarchical Network Model is proposed to study the problem of hierarchical relationships arising from different individuals in the economic domain. In the presented dynamically evolving network model, new directed edges are generated depending on the existing nodes and the hierarchical structures among the network, and these edges decay over time. When the preference of nodes in the network for higher ranks exceeds a certain threshold value, the equality state in the network becomes unstable and rank states emerge. Meanwhile, we select four real data sets for model evaluation and observe the resilience in the network hierarchy evolution and the differences formed by different patterns of hierarchy preference mechanisms, which help us better understand data science and network dynamics evolution. MDPI 2022-05-16 /pmc/articles/PMC9141125/ /pubmed/35626585 http://dx.doi.org/10.3390/e24050702 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
Yang, Xiaoteng
Wu, Zhenqiang
Javaid, Shumaila
An Adaptive Hierarchical Network Model for Studying the Structure of Economic Network
title An Adaptive Hierarchical Network Model for Studying the Structure of Economic Network
title_full An Adaptive Hierarchical Network Model for Studying the Structure of Economic Network
title_fullStr An Adaptive Hierarchical Network Model for Studying the Structure of Economic Network
title_full_unstemmed An Adaptive Hierarchical Network Model for Studying the Structure of Economic Network
title_short An Adaptive Hierarchical Network Model for Studying the Structure of Economic Network
title_sort adaptive hierarchical network model for studying the structure of economic network
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141125/
https://www.ncbi.nlm.nih.gov/pubmed/35626585
http://dx.doi.org/10.3390/e24050702
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