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The concept of nestedness, in particular for ecological and economical networks, has been introduced as a structural characteristic of real interacting systems. We suggest that the nestedness is in fact another way to express a mesoscale…

物理与社会 · 物理学 2016-02-22 Sang Hoon Lee

The observed architecture of ecological and socio-economic networks differs significantly from that of random networks. From a network science standpoint, non-random structural patterns observed in real networks call for an explanation of…

物理与社会 · 物理学 2019-05-30 Manuel Sebastian Mariani , Zhuo-Ming Ren , Jordi Bascompte , Claudio Juan Tessone

Understanding the causes and effects of network structural features is a key task in deciphering complex systems. In this context, the property of network nestedness has aroused a fair amount of interest as regards ecological networks.…

物理与社会 · 物理学 2013-09-23 Samuel Johnson , Virginia Dominguez-Garcia , Miguel A. Munoz

Breaking of equivalence between the microcanonical ensemble and the canonical ensemble, describing a large system subject to hard and soft constraints, respectively, was recently shown to occur in large random graphs. Hard constraints must…

概率论 · 数学 2017-06-06 Diego Garlaschelli , Frank den Hollander , Andrea Roccaverde

Nestedness characterizes the linkage pattern of networked systems, indicating the likelihood that a node is linked to the nodes linked to the nodes with larger degrees than it. Networks of mutualistic relationship between distinct groups of…

物理与社会 · 物理学 2012-03-13 Deok-Sun Lee , Seong Eun Maeng , Jae Woo Lee

The entropy of network ensembles characterizes the amount of information encoded in the network structure, and can be used to quantify network complexity, and the relevance of given structural properties observed in real network datasets…

无序系统与神经网络 · 物理学 2014-06-18 Kartik Anand , Dimitri Krioukov , Ginestra Bianconi

Nestedness is a common property of communication, finance, trade, and ecological networks. In networks with high levels of nestedness, the link positions of low-degree nodes (those with few links) form nested subsets of the link positions…

物理与社会 · 物理学 2023-12-19 Phillip P. A. Staniczenko , Debabrata Panja

A classic measure of ecological stability describes the tendency of a community to return to equilibrium after small perturbation. While many advances show how the network structure of these communities severely constrains such tendencies,…

种群与进化 · 定量生物学 2015-06-09 Gang Yan , Neo D. Martinez , Yang-Yu Liu

Mutualistic interactions, which are beneficial for both interacting species, are recurrently present in ecosystems. Observations of natural systems showed that, if we draw mutualistic relationships as binary links between species, the…

物理与社会 · 物理学 2019-08-21 Clàudia Payrató Borrás , Laura Hernández , Yamir Moreno

Nestedness is a property of interaction networks widely observed in natural mutualistic communities. Despite a widespread interest on this pattern, no general consensus exists on how to measure it. Instead, several metrics aiming at…

物理与社会 · 物理学 2020-02-04 Claudia Payrato-Borras , Laura Hernandez , Yamir Moreno

In this work we explore degree assortativity in complex networks, and extend its usual definition beyond that of nearest neighbours. We apply this definition to model networks, and describe a rewiring algorithm that induces assortativity.…

物理与社会 · 物理学 2024-06-04 Pádraig MacCarron , Shane Mannion , Thierry Platini

It is generally believed that, in the thermodynamic limit, the microcanonical description as a function of energy coincides with the canonical description as a function of temperature. However, various examples of systems for which the…

统计力学 · 物理学 2016-01-13 Tiziano Squartini , Joey de Mol , Frank den Hollander , Diego Garlaschelli

In this paper we generalize the concept of random networks to describe networks with non trivial features by a statistical mechanics approach. This framework is able to describe ensembles of undirected, directed as well as weighted…

无序系统与神经网络 · 物理学 2009-11-13 Ginestra Bianconi

In contrast to dyadic interactions, higher-order interactions may contain one another, with subgroups naturally embedded within larger groups. These containment patterns arise empirically in ecology, sociology, computer science and the…

Randomized network ensembles are the null models of real networks and are extensivelly used to compare a real system to a null hypothesis. In this paper we study network ensembles with the same degree distribution, the same…

无序系统与神经网络 · 物理学 2009-11-13 Ginestra Bianconi

Nestedness is a property of bipartite complex networks that has been shown to characterize the peculiar structure of biological and economical networks. In a nested network, a node of low degree has its neighborhood included in the…

网络与互联网体系结构 · 计算机科学 2023-12-18 Justin Loye , Sandrine Mouysset , Katia Jaffrès-Runser

Identifying and explaining the structure of complex networks at different scales has become an important problem across disciplines. At the mesoscale, modular architecture has attracted most of the attention. At the macroscale, other…

物理与社会 · 物理学 2018-11-09 María J. Palazzi , Javier Borge-Holthoefer , Claudio Tessone , Albert Solé-Ribalta

Network topology is a fundamental aspect of network science that allows us to gather insights into the complicated relational architectures of the world we inhabit. We provide a first specific study of neighbourhood degree sequences in…

社会与信息网络 · 计算机科学 2019-06-11 Keith M. Smith

Degree heterogeneity and latent geometry, also referred to as popularity and similarity, are key explanatory components underlying the structure of real-world networks. The relationship between these components and the statistical…

社会与信息网络 · 计算机科学 2024-09-18 Keith Malcolm Smith , Jason P. Smith

Triangles are an important building block and distinguishing feature of real-world networks, but their structure is still poorly understood. Despite numerous reports on the abundance of triangles, there is very little information on what…

社会与信息网络 · 计算机科学 2013-03-06 Nurcan Durak , Ali Pinar , Tamara G. Kolda , C. Seshadhri
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