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Networks are widely used to represent interaction pattern among the components in complex systems. Structures of real networks from differ- ent domains may vary quite significantly. Since there is an interplay be- tween network architecture…

Quantitative Methods · Quantitative Biology 2016-05-10 Krishanu Deyasi , Shashankaditya Upadhyay , Anirban Banerjee

Networks are powerful tools for modeling interactions in complex systems. While traditional networks use scalar edge weights, many real-world systems involve multidimensional interactions. For example, in social networks, individuals often…

Social and Information Networks · Computer Science 2024-10-08 Yu Tian , Sadamori Kojaku , Hiroki Sayama , Renaud Lambiotte

This paper aims at addressing distributed averaging problems for signed networks in the presence of general directed topologies that are represented by signed digraphs. A new class of improved Laplacian potential functions is proposed by…

Optimization and Control · Mathematics 2020-08-14 Mingjun Du , Deyuan Meng , Zheng-Guang Wu

Genetic regulatory networks (GRNs) have been widely studied, yet there is a lack of understanding with regards to the final size and properties of these networks, mainly due to no network currently being complete. In this study, we analyzed…

Molecular Networks · Quantitative Biology 2019-03-13 Adrian I. Campos-González , Julio A. Freyre-González

We study a generic family of nonlinear dynamics on undirected networks generalising linear consensus. We find a compact expression for its equilibrium points in terms of the topology of the network and classify their stability using the…

Dynamical Systems · Mathematics 2021-12-07 Marc Homs-Dones , Karel Devriendt , Renaud Lambiotte

Signed network embedding is an approach to learn low-dimensional representations of nodes in signed networks with both positive and negative links, which facilitates downstream tasks such as link prediction with general data mining…

Social and Information Networks · Computer Science 2021-04-30 Dengcheng Yan , Youwen Zhang , Wei Li , Yiwen Zhang

Many complex systems - be they financial, natural, or social - are composed of units - such as stocks, neurons, or agents - whose joint activity can be represented as a multivariate time series. An issue of both practical and theoretical…

A number of network structural characteristics have recently been the subject of particularly intense research, including degree distributions, community structure, and various measures of vertex centrality, to mention only a few. Vertices…

Social and Information Networks · Computer Science 2016-03-23 Igor Trpevski , Tamara Dimitrova , Tommy Boshkovski , Ljupco Kocarev

Stars and cycles are basic structures in network construction. The former has been well studied in network analysis, while the latter attracted rare attention. A node together with its neighbors constitute a neighborhood star-structure…

Physics and Society · Physics 2019-03-13 Tianlong Fan , Linyuan Lü , Dinghua Shi

The structure of a complex network plays a crucial role in determining its dynamical properties. In this work, we show that the the degree to which a network is directed and hierarchically organised is closely associated with the degree to…

A signed graph is a graph whose edges are labelled positive or negative. The sign of a circle (cycle, circuit) is the product of the signs of its edges. Most of the essential properties of a signed graph depend on the signs of its circles.…

Combinatorics · Mathematics 2021-06-16 Thomas Zaslavsky

We study online social networks in which relationships can be either positive (indicating relations such as friendship) or negative (indicating relations such as opposition or antagonism). Such a mix of positive and negative links arise in…

Physics and Society · Physics 2010-03-15 Jure Leskovec , Daniel Huttenlocher , Jon Kleinberg

We study the evolution of social networks that contain both friendly and unfriendly pairwise links between individual nodes. The network is endowed with dynamics in which the sense of a link in an imbalanced triad--a triangular loop with 1…

Statistical Mechanics · Physics 2007-05-23 T. Antal , P. L. Krapivsky , S. Redner

Network theory provides a rich toolbox consisting of methods, measures, and models for studying the structure and dynamics of complex systems found in nature, society, or technology. Recently, it has been pointed out that many real-world…

Physics and Society · Physics 2016-04-07 Marc Wiedermann , Jonathan F. Donges , Jobst Heitzig , Jürgen Kurths

A majority of real life networks are weighted and sparse. The present article aims at characterization of weighted networks based on sparsity, as a measure of inherent diversity, of different network parameters. It utilizes sparsity index…

Discrete Mathematics · Computer Science 2021-01-12 Swati Goswami , Asit K. Das , Subhas C. Nandy

We review the recent fast progress in statistical physics of evolving networks. Interest has focused mainly on the structural properties of random complex networks in communications, biology, social sciences and economics. A number of giant…

Statistical Mechanics · Physics 2015-06-24 S. N. Dorogovtsev , J. F. F. Mendes

A class of networks are those with both positive and negative links. In this manuscript, we studied the interplay between positive and negative ties on mesoscopic level of these networks, i.e., their community structure. A community is…

Physics and Society · Physics 2018-09-05 Pouya Esmailian , Seyed Ebrahim Abtahi , Mahdi Jalili

Signed networks capture the polarity of relationships between nodes, providing valuable insights into complex systems where both supportive and antagonistic interactions play a critical role in shaping the network dynamics. We propose a…

Methodology · Statistics 2026-03-05 Alberto Caimo , Isabella Gollini

Over the last two decades, network theory has shown to be a fruitful paradigm in understanding the organization and functioning of real-world complex systems. One technique helpful to this endeavor is identifying functionally influential…

Physics and Society · Physics 2022-01-24 Francesco Picciolo , Franco Ruzzenenti , Petter Holme , Rossana Mastrandrea

Graph convolutional networks (GCNs) and its variants are designed for unsigned graphs containing only positive links. Many existing GCNs have been derived from the spectral domain analysis of signals lying over (unsigned) graphs and in each…

Machine Learning · Computer Science 2022-08-16 Rahul Singh , Yongxin Chen