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Degree distribution, or equivalently called degree sequence, has been commonly used to be one of most significant measures for studying a large number of complex networks with which some well-known results have been obtained. By contrast,…

Physics and Society · Physics 2020-02-19 Fei Ma , Xiaoming Wang , Ping Wang

In this work we present a model for evolving networks, where the driven force is related to the social affinity between individuals in a population. In the model, a set of individuals initially arranged on a regular ordered network and thus…

Adaptation and Self-Organizing Systems · Physics 2009-11-13 B. Ruyu , M. N. Kuperman

This article formalizes the problem of modeling social networks into an interacting particle system on random geometric graphs. Each vertex of the graph is associated with a geometric position in a latent space describing the unobserved…

Probability · Mathematics 2021-11-03 Khader Khadraoui , Ahmed Sid-Ali

We consider two classes of random graphs: $(a)$ Poissonian random graphs in which the $n$ vertices in the graph have i.i.d.\ weights distributed as $X$, where $\mathbb{E}(X) = \mu$. Edges are added according to a product measure and the…

Probability · Mathematics 2010-10-05 Tom Britton , Pieter Trapman

Preferential attachment is an appealing edge generating mechanism for modeling social networks. It provides both an intuitive description of network growth and an explanation for the observed power laws in degree distributions. However,…

Methodology · Statistics 2017-12-21 Phyllis Wan , Tiandong Wang , Richard A. Davis , Sidney I. Resnick

Much recent research activity has been devoted to empirical study and theoretical models of complex networks (random graphs) with three qualitative features: power-law degree distribution, local clustering of edges, and small diameter. We…

Disordered Systems and Neural Networks · Physics 2017-08-23 David J. Aldous

Scale-free (SF) networks and small world networks have been found to occur in very diverse contexts. It is this striking universality which makes one look for widely applicable mechanisms which lead to the formation of such networks. In…

Disordered Systems and Neural Networks · Physics 2007-05-23 Markus Brede , John Finnigan

We introduce a simple network model that is inspired by social information networks such as twitter. Agents are nodes, connecting to another agent by building a directed edge has a cost, and reaching other agents via short directed paths…

Computer Science and Game Theory · Computer Science 2017-05-10 L. Elisa Celis , Aida S. Mousavifar

This doctoral work focuses on three main problems related to social networks: (1) Orchestrating Network Formation: We consider the problem of orchestrating formation of a social network having a certain given topology that may be desirable…

Social and Information Networks · Computer Science 2017-06-29 Swapnil Dhamal

Motifs are the fundamental components of complex systems. The topological structure of networks representing complex systems and the frequency and distribution of motifs in these networks are intertwined. The complexities associated with…

Social and Information Networks · Computer Science 2020-05-21 Ali Jazayeri , Christopher C. Yang

Dynamical processes, such as the diffusion of knowledge, opinions, pathogens, "fake news", innovation, and others, are highly dependent on the structure of the social network on which they occur. However, questions on why most social…

Physics and Society · Physics 2020-05-13 Demival Vasques Filho , Dion R. J. O'Neale

We study the family of network models derived by requiring the expected properties of a graph ensemble to match a given set of measurements of a real-world network, while maximizing the entropy of the ensemble. Models of this type play the…

Statistical Mechanics · Physics 2009-11-10 Juyong Park , M. E. J. Newman

This paper analyzes key properties of networks generated by geometric preferential attachment. We establish that the expected number of triangles is proportional to that of the standard preferential attachment model, with a proportionality…

Probability · Mathematics 2025-11-25 Chenxu Feng , Yifan Li

We introduce a representation of any atom in any chemical environment for the generation of efficient quantum machine learning (QML) models of common electronic ground-state properties. The representation is based on scaled distribution…

Chemical Physics · Physics 2018-04-18 Felix A. Faber , Anders S. Christensen , Bing Huang , O. Anatole von Lilienfeld

A defining feature of many large empirical networks is their intrinsic complexity. However, many networks also contain a large degree of structural repetition. An immediate question then arises: can we characterize essential network…

Physics and Society · Physics 2008-10-09 Yanghua Xiao , Ben D. MacArthur , Hui Wang , Momiao Xiong , Wei Wang

Since some realistic networks are influenced not only by increment behavior but also by tunable clustering mechanism with new nodes to be added to networks, it is interesting to characterize the model for those actual networks. In this…

Physics and Society · Physics 2012-02-03 Ying-Hong Ma , Huijia Li , Xiao-Dong Zhang

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

We study a weighted-set graph coloring problem in which one assigns $q$ colors to the vertices of a graph such that adjacent vertices have different colors, with a vertex weighting $w$ that either disfavors or favors a given subset of $s$…

Mathematical Physics · Physics 2011-08-19 Robert Shrock , Yan Xu

A wide range of interacting systems can be described by complex networks. A common feature of such networks is that they consist of several communities or modules, the degree of which may quantified as the \emph{modularity}. However, even a…

Statistical Mechanics · Physics 2015-06-19 Jae Sung Lee , Sungmin Hwang , Joonhyun Yeo , Doochul Kim , Byungnam Kahng

Through a redefinition of patterns in an Hopfield-like model, we introduce and develop an approach to model discrete systems made up of many, interacting components with inner degrees of freedom. Our approach clarifies the intrinsic…

Statistical Mechanics · Physics 2015-05-19 Elena Agliari , Adriano Barra