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Many real networks are complex and have power-law vertex degree distribution, short diameter, and high clustering. We analyze the network model based on thresholding of the summed vertex weights, which belongs to the class of networks…

Other Condensed Matter · Physics 2007-05-23 Naoki Masuda , Hiroyoshi Miwa , Norio Konno

Network structures are extremely important to the study of political science. Much of the data in its subfields are naturally represented as networks. This includes trade, diplomatic and conflict relationships. The social structure of…

Methodology · Statistics 2011-05-05 Drew Conway

Although the community structure organization is one of the most important characteristics of real-world networks, the traditional network models fail to reproduce the feature. Therefore, the models are useless as benchmark graphs for…

Physics and Society · Physics 2014-04-08 Piotr Fronczak , Agata Fronczak , Maksymilian Bujok

Many real-world networks exhibit scale-free feature, have a small diameter and a high clustering tendency. We have studied the properties of a growing network, which has all these features, in which an incoming node is connected to its…

Statistical Mechanics · Physics 2009-11-10 Parongama Sen , S. S. Manna

The Watts-Strogatz algorithm of transferring the square lattice to a small world network is modified by introducing preferential rewiring constrained by connectivity demand. The evolution of the network is two-step: sequential preferential…

Statistical Mechanics · Physics 2009-11-11 Danuta Makowiec

Identifying power-law scaling in real networks - indicative of preferential attachment - has proved controversial. Critics argue that measuring the temporal evolution of a network directly is better than measuring the degree distribution…

What is the underlying mechanism leading to power-law degree distributions of many natural and artificial networks is still at issue. We consider that scale-free networks emerges from self-organizing process, and such a evolving model is…

Statistical Mechanics · Physics 2007-05-23 Gang Yan , Tao Zhou , Ying-Di Jin , Zhong-Qian Fu

Many complex systems--from social and communication networks to biological networks and the Internet--are thought to exhibit scale-free structure. However, prevailing explanations rely on the constant addition of new nodes, an assumption…

Adaptation and Self-Organizing Systems · Physics 2022-11-10 Christopher W. Lynn , Caroline M. Holmes , Stephanie E. Palmer

We investigate the degree distribution $P(k)$ and the clustering coefficient $C$ of the line graphs constructed on the Erd\"os-R\'enyi networks, the exponential and the scale-free growing networks. We show that the character of the degree…

Computational Physics · Physics 2015-05-13 Anna Manka-Krason , Advera Mwijage , Krzysztof Kulakowski

The past decade has seen tremendous growth in the field of Complex Social Networks. Several network generation models have been extensively studied to develop an understanding of how real world networks evolve over time. Two important…

Social and Information Networks · Computer Science 2017-01-23 Muhammad Qasim Pasta , Faraz Zaidi

Research in network science has shown that many naturally occurring and technologically constructed networks are scale free, that means a power law degree distribution emerges from a growth model in which each new node attaches to the…

Physics and Society · Physics 2009-11-11 Michael Schnegg

We present a general class of geometric network growth mechanisms by homogeneous attachment in which the links created at a given time $t$ are distributed homogeneously between a new node and the exising nodes selected uniformly. This is…

Physics and Society · Physics 2018-03-28 Charles Murphy , Antoine Allard , Edward Laurence , Guillaume St-Onge , Louis J. Dubé

Many real world networks, such as social networks, are primarily formed through local interactions between agents. Additionally, in contrast with common network models, social and biological networks exhibit a high degree of clustering.…

Physics and Society · Physics 2015-03-10 Navid Dianati , Nima Dehmamy

Real world complex networks are scale free and possess meso-scale properties like core-periphery and community structure. We study evolution of the core over time in real world networks. This paper proposes evolving models for both…

Social and Information Networks · Computer Science 2015-12-01 Akrati Saxena , S. R. S. Iyengar

Motivated by a recently introduced network growth mechanism that rely on the ranking of node prestige measures [S. Fortunato \emph{et al}., Phys. Rev. Lett. \textbf{96}, 218701 (2006)], a rank-based model for weighted network evolution is…

Disordered Systems and Neural Networks · Physics 2015-06-25 Liang Tian , Da-Ning Shi , Chen-Ping Zhu

A degree-corrected distribution-free model is proposed for weighted social networks with latent structural information. The model extends the previous distribution-free models by considering variation in node degree to fit real-world…

Social and Information Networks · Computer Science 2024-04-08 Huan Qing

Generative mechanisms which lead to empirically observed structure of networked systems from diverse fields like biology, technology and social sciences form a very important part of study of complex networks. The structure of many…

Physics and Society · Physics 2015-12-03 Snehal M. Shekatkar , G. Ambika

Many social, technological, biological, and economical systems are best described by weighted networks, whose properties and dynamics depend not only on their structures but also on the connection weights among their nodes. However, most…

Disordered Systems and Neural Networks · Physics 2015-06-24 Chunguang Li , Guanrong Chen

In a highly influential paper twenty years ago, Barab\'asi and Albert [Science 286, 509 (1999)] showed that networks undergoing generic growth processes with preferential attachment evolve towards scale-free structures. In any finite…

Physics and Society · Physics 2020-09-08 Ido Tishby , Ofer Biham , Eytan Katzav

Can one hear the 'sound' of a growing network? We address the problem of recognizing the topology of evolving biological or social networks. Starting from percolation theory, we analytically prove a linear inverse relationship between two…

Quantitative Methods · Quantitative Biology 2014-04-10 Ashish Bhan , Animesh Ray
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