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相关论文: The Evolution of Interpersonal Relationships in a …

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A simple model is proposed to simulate the evolution of interpersonal relationships in a class. The small social network is simply assumed as an undirected and weighted graph, in which students are represented by vertices, and the extent of…

其他凝聚态物理 · 物理学 2007-05-23 Bo Hu , Xin-Yu Jiang , Jun-Feng Ding , Yan-Bo Xie , Bing-Hong Wang

A social network grows over a period of time with the formation of new connections and relations. In recent years we have witnessed a massive growth of online social networks like Facebook, Twitter etc. So it has become a problem of extreme…

社会与信息网络 · 计算机科学 2015-09-25 Amit Kumar Verma , Manjish Pal

The goal of this paper is to provide mathematically rigorous tools for modelling the evolution of a community of interacting individuals. We model the population by a measure space where the measure determines the abundance of individual…

概率论 · 数学 2017-05-17 Thomas Cass , Terry Lyons

Many social and biological networks consist of communities - groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting…

物理与社会 · 物理学 2009-11-11 Chunguang Li , Philip K. Maini

We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement…

统计力学 · 物理学 2009-11-10 Alain Barrat , Marc Barthelemy , Alessandro Vespignani

The personal network of relationships is structured in circles of friendships, that go from the most intense relationships to the least intense ones. While this is a well established result, little is known about the stability of those…

Groups - social communities are important components of entire societies, analysed by means of the social network concept. Their immanent feature is continuous evolution over time. If we know how groups in the social network has evolved we…

社会与信息网络 · 计算机科学 2012-10-19 Piotr Bródka , Przemysław Kazienko , Bartosz Kołoszczyk

We propose a dynamical model for group formation and switching behavior in systems where each group competes for members through attraction functions that are inversely proportional to their current sizes. This attraction is modulated by…

动力系统 · 数学 2026-03-12 Samit Ghosh

In this paper we show that the small world and weak ties phenomena can spontaneously emerge in a social network of interacting agents. This dynamics is simulated in the framework of a simplified model of opinion diffusion in an evolving…

物理与社会 · 物理学 2014-01-10 T. Carletti , D. Fanelli , S. Righi

Understanding how cooperation evolves in structured populations remains a fundamental question across diverse disciplines. The problem of cooperation typically involves pairwise or group interactions among individuals. While prior studies…

物理与社会 · 物理学 2025-06-26 Dini Wang , Peng Yi , Gang Yan , Feng Fu

Graph vertices are often organized into groups that seem to live fairly independently of the rest of the graph, with which they share but a few edges, whereas the relationships between group members are stronger, as shown by the large…

物理与社会 · 物理学 2007-12-20 Santo Fortunato , Claudio Castellano

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 societies are organized in networks that are formed by people who meet and interact over time. In this paper, we present a first model to capture the micro-foundations of social networks evolution, where boundedly rational agents of…

社会与信息网络 · 计算机科学 2015-08-17 Ahmed M. Alaa , Kartik Ahuja , Mihaela van der Schaar

Relationships between people constantly evolve, altering interpersonal behavior and defining social groups. Relationships between nodes in social networks can be represented by a tie strength, often empirically assessed using surveys. While…

社会与信息网络 · 计算机科学 2021-01-26 James Flamino , Ross DeVito , Boleslaw K. Szymanski , Omar Lizardo

Random graphs are useful tools to study social interactions. In particular, the use of weighted random graphs allows to handle a high level of information concerning which agents interact and in which degree the interactions take place.…

物理与社会 · 物理学 2009-11-13 Jose J. Ramasco

Topology and weights are closely related in weighted complex networks and this is reflected in their modular structure. We present a simple network model where the weights are generated dynamically and they shape the developing topology. By…

物理与社会 · 物理学 2008-01-30 J. M. Kumpula , J. -P. Onnela , J. Saramaki , K. Kaski , J. Kertesz

The seceder model illustrates how the desire to be different than the average can lead to formation of groups in a population. We turn the original, agent based, seceder model into a model of network evolution. We find that the structural…

无序系统与神经网络 · 物理学 2007-05-23 Andreas Gronlund , Petter Holme

While actors in a population can interact with anyone else freely, social relations significantly influence our inclination towards particular individuals. The consequence of such interactions, however, may also form the intensity of our…

物理与社会 · 物理学 2024-04-24 Xiaojin Xiong , Ziyan Zeng , Minyu Feng , Attila Szolnoki

Modeling human dynamics responsible for the formation and evolution of the so-called social networks - structures comprised of individuals or organizations and indicating connectivities existing in a community - is a topic recently…

计算机与社会 · 计算机科学 2007-05-23 Victor V. Kryssanov , Frank J. Rinaldo , Evgeny L. Kuleshov , Hitoshi Ogawa

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…

适应与自组织系统 · 物理学 2009-11-13 B. Ruyu , M. N. Kuperman
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