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相关论文: Modeling the Dynamics of Social Networks

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The increasing availability of large-scale data on human behavior has catalyzed simultaneous advances in network theory, capturing the scaling properties of the interactions between a large number of individuals, and human dynamics,…

物理与社会 · 物理学 2013-04-10 Chaoming Song , Dashun Wang , Albert-Laszlo Barabasi

Complex networks as the World Wide Web, the web of human sexual contacts or criminal networks often do not have an engineered architecture but instead are self-organized by the actions of a large number of individuals. From these local…

无序系统与神经网络 · 物理学 2007-05-23 Holger Ebel , Joern Davidsen , Stefan Bornholdt

The structure and dynamic of social network are largely determined by the heterogeneous interaction activity and social capital allocation of individuals. These features interplay in a non-trivial way in the formation of network and…

Temporal networks of face-to-face interactions between individuals are useful proxies of the dynamics of social systems on fast time scales. Several empirical statistical properties of these networks have been shown to be robust across a…

物理与社会 · 物理学 2023-02-03 Didier Le Bail , Mathieu Génois , Alain Barrat

We consider a dynamic social network model in which agents play repeated games in pairings determined by a stochastically evolving social network. Individual agents begin to interact at random, with the interactions modeled as games. The…

概率论 · 数学 2007-05-23 Brian Skyrms , Robin Pemantle

What drives the propensity for the social network dynamics? Social influence is believed to drive both off-line and on-line human behavior, however it has not been considered as a driver of social network evolution. Our analysis suggest…

物理与社会 · 物理学 2016-05-27 Yang Yang , Nitesh V. Chawla , Ryan N. Lichtenwalter , Yuxiao Dong

Recent years saw an increased interest in modeling and understanding the mechanisms of opinion and innovation spread through human networks. Using analysis of real-world social data, researchers are able to gain a better understanding of…

社会与信息网络 · 计算机科学 2016-03-29 Ajay Saini , Natasha Markuzon

Modularity structures are common in various social and biological networks. However, its dynamical origin remains an open question. In this work, we set up a dynamical model describing the evolution of a social network. Based on the…

物理与社会 · 物理学 2011-08-19 Menghui Li , Shuguang Guan , Choy-Heng Lai

Over the past decade network theory has turned out to be a powerful methodology to investigate complex systems of various sorts. Through data analysis, modeling, and simulation quite an unparalleled insight into their structure, function,…

物理与社会 · 物理学 2010-07-16 Kimmo Kaski

In recent years, we have observed a significant trend towards filling the gap between social network analysis and control. This trend was enabled by the introduction of new mathematical models describing dynamics of social groups, the…

系统与控制 · 计算机科学 2017-10-16 Anton V. Proskurnikov , Roberto Tempo

Models of cooperation grounded on social networks and on the ability of individuals to choose actions and partners aim to describe human social behavior. Extensive computer simulations of these models give important insight in the social…

物理与社会 · 物理学 2007-05-23 Victor M. Eguluz , Martin G. Zimmermann , Camilo J. Cela-Conde , Maxi San Miguel

In this thesis we contribute to the understanding of the pivotal role of the temporal dimension in networked social systems, previously neglected and now uncovered by the data revolution recently blossomed in this field. To this aim, we…

物理与社会 · 物理学 2016-08-15 Michele Starnini

In communication networks structure and dynamics are tightly coupled. The structure controls the flow of information and is itself shaped by the dynamical process of information exchanged between nodes. In order to reconcile structure and…

物理与社会 · 物理学 2013-04-08 Jan O. Haerter , Bjorn Jamtveit , Joachim Mathiesen

Human behavior often exhibit a scheme in which individuals adopt indifferent, neutral, or radical positions on a given topic. The mechanisms leading to community formation are strongly related with social pressure and the topology of the…

物理与社会 · 物理学 2013-02-21 Marta Balbás Gambra , Erwin Frey

Networks built to model real world phenomena are characeterised by some properties that have attracted the attention of the scientific community: (i) they are organised according to community structure and (ii) their structure evolves with…

社会与信息网络 · 计算机科学 2019-09-04 Giulio Rossetti , Rémy Cazabet

Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of…

社会与信息网络 · 计算机科学 2014-09-18 Frédéric Gilbert , Paolo Simonetto , Faraz Zaidi , Fabien Jourdan , Romain Bourqui

Temporal social networks of human interactions are preponderant in understanding the fundamental patterns of human behavior. In these networks, interactions occur locally between individuals (i.e., nodes) who connect with each other at…

物理与社会 · 物理学 2022-10-11 Shaunette T. Ferguson , Teruyoshi Kobayashi

Representing social systems as networks, starting from the interactions between individuals, sheds light on the mechanisms governing their dynamics. However, networks encode only pairwise interactions, while most social interactions occur…

物理与社会 · 物理学 2024-08-29 Iacopo Iacopini , Márton Karsai , Alain Barrat

Many real-world complex systems such as social, biological, information as well as technological systems results of a decentralized and unplanned evolution which leads to a common structuration. Irrespective of their origin, these so-called…

社会与信息网络 · 计算机科学 2013-05-03 Chantal Cherifi , Jean-François Santucci

Studies on social networks have proved that endogenous and exogenous factors influence dynamics. Two streams of modeling exist on explaining the dynamics of social networks: 1) models predicting links through network properties, and 2)…

社会与信息网络 · 计算机科学 2012-10-22 Julie M. Birkholz , Rena Bakhshi , Ravindra Harige , Maarten van Steen , Peter Groenewegen
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