区间加权网络中的中心性测度

IF 2.2 4区 数学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Hélder Alves;Paula Brito;Pedro Campos
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引用次数: 3

摘要

中心性度量在网络科学中用于评估顶点的中心性或它们在网络中的位置。根据某些标准,存在大量的中心性度量。然而,加权网络的最著名的中心性度量、度中心性、贴近度中心性和介数中心性的推广仅假设边缘权重是常数。本文提出了一种方法来推广度、贴近度和介数中心性,考虑到边缘权重以闭合区间(区间加权网络,IWN)的形式变化。我们将我们的中心性度量方法应用于两个真实世界的IWN。第一个是葡萄牙大陆的通勤网络,位于23个NUTS 3地区之间。第二个重点是2003年至2015年28个欧洲国家之间的年度商品贸易。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Centrality measures in interval-weighted networks
Centrality measures are used in network science to assess the centrality of vertices or the position they occupy in a network. There are a large number of centrality measures according to some criterion. However, the generalizations of the most well-known centrality measures for weighted networks, degree centrality, closeness centrality and betweenness centrality have solely assumed the edge weights to be constants. This article proposes a methodology to generalize degree, closeness and betweenness centralities taking into account the variability of edge weights in the form of closed intervals (interval-weighted networks, IWN). We apply our centrality measures approach to two real-world IWN. The first is a commuter network in mainland Portugal, between the 23 NUTS 3 Regions. The second focuses on annual merchandise trade between 28 European countries, from 2003 to 2015.
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来源期刊
Journal of complex networks
Journal of complex networks MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.20
自引率
9.50%
发文量
40
期刊介绍: Journal of Complex Networks publishes original articles and reviews with a significant contribution to the analysis and understanding of complex networks and its applications in diverse fields. Complex networks are loosely defined as networks with nontrivial topology and dynamics, which appear as the skeletons of complex systems in the real-world. The journal covers everything from the basic mathematical, physical and computational principles needed for studying complex networks to their applications leading to predictive models in molecular, biological, ecological, informational, engineering, social, technological and other systems. It includes, but is not limited to, the following topics: - Mathematical and numerical analysis of networks - Network theory and computer sciences - Structural analysis of networks - Dynamics on networks - Physical models on networks - Networks and epidemiology - Social, socio-economic and political networks - Ecological networks - Technological and infrastructural networks - Brain and tissue networks - Biological and molecular networks - Spatial networks - Techno-social networks i.e. online social networks, social networking sites, social media - Other applications of networks - Evolving networks - Multilayer networks - Game theory on networks - Biomedicine related networks - Animal social networks - Climate networks - Cognitive, language and informational network
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