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Why are most empirical networks, with the prominent exception of social ones, generically degree-degree anticorrelated, i.e. disassortative? With a view to answering this long-standing question, we define a general class of degree-degree…

Statistical Mechanics · Physics 2010-03-16 Samuel Johnson , Joaquin J. Torres , J. Marro , Miguel A. Munoz

We study synchronization phenomena in scale-free networks of asymetrically coupled dynamical systems featuring degree-degree correlation in the connection wiring. We show that when the interaction is dominant from the high-degree to the…

Disordered Systems and Neural Networks · Physics 2009-11-11 F. Sorrentino , M. di Bernardo , G. Huerta Cuellar , S. Boccaletti

We present a continuous formulation of epidemic spreading on multilayer networks using a tensorial representation, extending the models of monoplex networks to this context. We derive analytical expressions for the epidemic threshold of the…

We study the effect of assortative and disassortative mixing on the robustness of networks under random node failures. For ordinary (dyadic) networks, by using the generating function technique and stochastic simulations, we show that the…

Physics and Society · Physics 2026-04-16 L. D. Valdez , C. E. La Rocca

In this paper we examine the percolation properties of higher-order networks that have non-trivial clustering and subgraph-based assortative mixing (the tendency of vertices to connect to other vertices based on subgraph joint degree). Our…

Physics and Society · Physics 2022-10-07 Peter Mann , Lei Fang , Simon Dobson

Complex systems are characterized by many interacting units that give rise to emergent behavior. A particularly advantageous way to study these systems is through the analysis of the networks that encode the interactions among the system's…

Physics and Society · Physics 2019-03-21 Alberto Aleta , Yamir Moreno

In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time, and include other types of complications. Such systems include…

Physics and Society · Physics 2014-08-28 Mikko Kivelä , Alexandre Arenas , Marc Barthelemy , James P. Gleeson , Yamir Moreno , Mason A. Porter

The study of spreading processes often analyzes networks at different resolutions, e.g., at the level of individuals or countries, but it is not always clear how properties at one resolution can carry over to another. Accordingly, in this…

Physics and Society · Physics 2024-12-04 Baike She , Matthew Hale

Many real-world complex systems consist of a set of elementary units connected by relationships of different kinds. All such systems are better described in terms of multiplex networks, where the links at each layer represent a different…

Physics and Society · Physics 2014-03-17 Federico Battiston , Vincenzo Nicosia , Vito Latora

Different graph generalizations have been recently used in an ad-hoc manner to represent multilayer networks, i.e. systems formed by distinct layers where each layer can be seen as a network. Similar constructions have also been used to…

Discrete Mathematics · Computer Science 2016-09-30 Klaus Wehmuth , Éric Fleury , Artur Ziviani

We obtain the clustering coefficient, the degree-dependent local clustering, and the mean clustering of networks with arbitrary correlations between the degrees of the nearest-neighbor vertices. The resulting formulas allow one to determine…

Statistical Mechanics · Physics 2009-11-10 S. N. Dorogovtsev

Many processes of spreading and diffusion take place on temporal networks, and their outcomes are influenced by correlations in the times of contact. These correlations have a particularly strong influence on processes where the spreading…

Physics and Society · Physics 2017-09-19 Mikko Kivelä , Jordan Cambe , Jari Saramäki , Márton Karsai

We find that traditional statistics for measuring degree mixing are strongly affected by superrich nodes. To counteract and measure the effect of superrich nodes, we propose a paradigm to quantify the mixing pattern of a real network in…

Physics and Society · Physics 2015-05-14 Xiao-Ke Xu , Jie Zhang , Junfeng Sun , Michael Small

Multilayer networks preserve full information about the different interactions among the constituents of a complex system, and have recently proven quite useful in modelling transportation networks, social circles, and the human brain. A…

Physics and Society · Physics 2020-06-29 Andrea Santoro , Vincenzo Nicosia

Our work is motivated by and illustrated with application of association networks in computational biology, specifically in the context of gene/protein regulatory networks. Association networks represent systems of interacting elements,…

Applications · Statistics 2012-05-01 Natallia Katenka , Eric D. Kolaczyk

The purpose of this paper is to assess the statistical characterization of weighted networks in terms of the generalization of the relevant parameters, namely average path length, degree distribution and clustering coefficient. Although the…

Physics and Society · Physics 2007-05-23 Antoniou Ioannis , Tsompa Eleni

Inspired by studies on airline networks we propose a general model for weighted networks in which topological growth and weight dynamics are both determined by cost adversarial mechanism. Since transportation networks are designed and…

Physics and Society · Physics 2007-12-10 Yihong Hu , Daoli Zhu , Yang Li , Bing Su , Bingxin Zhu

The degree distribution is an important characteristic of complex networks. In many applications, quantification of degree distribution in the form of a fixed-length feature vector is a necessary step. On the other hand, we often need to…

Social and Information Networks · Computer Science 2013-12-24 Sadegh Aliakbary , Jafar Habibi , Ali Movaghar

We discuss three related models of scale-free networks with the same degree distribution but different correlation properties. Starting from the Barabasi-Albert construction based on growth and preferential attachment we discuss two other…

Statistical Mechanics · Physics 2009-11-10 R. Xulvi-Brunet , W. Pietsch , I. M. Sokolov

Multiplex networks are convenient mathematical representations for many real-world -- biological, social, and technological -- systems of interacting elements, where pairwise interactions among elements have different flavors. Previous…

Physics and Society · Physics 2020-05-26 Saeed Osat , Filippo Radicchi , Fragkiskos Papadopoulos