中文
相关论文

相关论文: The Network of Collaboration Among Rappers and its…

200 篇论文

Based on an expert systems approach, the issue of community detection can be conceptualized as a clustering model for networks. Building upon this further, community structure can be measured through a clustering coefficient, which is…

社会与信息网络 · 计算机科学 2019-04-12 Roy Cerqueti , Giovanna Ferraro , Antonio Iovanella

Many networks are important because they are substrates for dynamical systems, and their pattern of functional connectivity can itself be dynamic -- they can functionally reorganize, even if their underlying anatomical structure remains…

神经元与认知 · 定量生物学 2010-04-21 Cosma Rohilla Shalizi , Marcelo F. Camperi , Kristina Lisa Klinkner

Networks have become a key approach to understanding systems of interacting objects, unifying the study of diverse phenomena including biological organisms and human society. One crucial step when studying the structure and dynamics of…

物理与社会 · 物理学 2010-09-16 Yong-Yeol Ahn , James P. Bagrow , Sune Lehmann

This paper focuses on the modeling of musical melodies as networks. Notes of a melody can be treated as nodes of a network. Connections are created whenever notes are played in sequence. We analyze some main tracks coming from different…

声音 · 计算机科学 2017-09-29 Stefano Ferretti

Many empirical networks have community structure, in which nodes are densely interconnected within each community (i.e., a group of nodes) and sparsely across different communities. Like other local and meso-scale structure of networks,…

物理与社会 · 物理学 2018-05-10 Sadamori Kojaku , Naoki Masuda

To find interesting structure in networks, community detection algorithms have to take into account not only the network topology, but also dynamics of interactions between nodes. We investigate this claim using the paradigm of…

社会与信息网络 · 计算机科学 2012-03-19 Rumi Ghosh , Kristina Lerman

In this paper, I argue that we can better understand the relationship between social structure and materiality by combining qualitative analysis of practices in shared physical space with statistical analysis. Drawing on the two-mode…

计算机与社会 · 计算机科学 2018-07-23 Nikita Basov

Many methods have been proposed for community detection in networks, but most of them do not take into account additional information on the nodes that is often available in practice. In this paper, we propose a new joint community…

机器学习 · 统计学 2016-12-13 Yuan Zhang , Elizaveta Levina , Ji Zhu

Given a social network, which of its nodes have a stronger impact in determining its structure? More formally: which node-removal order has the greatest impact on the network structure? We approach this well-known problem for the first time…

社会与信息网络 · 计算机科学 2011-10-21 Paolo Boldi , Marco Rosa , Sebastiano Vigna

Due to notable discoveries in the fast evolving field of complex networks, recent research in software engineering has also focused on representing software systems with networks. Previous work has observed that these networks follow…

社会与信息网络 · 计算机科学 2011-05-24 Lovro Šubelj , Marko Bajec

Uncovering the community structure exhibited by real networks is a crucial step towards an understanding of complex systems that goes beyond the local organization of their constituents. Many algorithms have been proposed so far, but none…

物理与社会 · 物理学 2010-09-17 Andrea Lancichinetti , Santo Fortunato

We consider the problem of detecting communities or modules in networks, groups of vertices with a higher-than-average density of edges connecting them. Previous work indicates that a robust approach to this problem is the maximization of…

数据分析、统计与概率 · 物理学 2007-05-23 M. E. J. Newman

Community or modular structure is considered to be a significant property of large scale real-world graphs such as social or information networks. Detecting influential clusters or communities in these graphs is a problem of considerable…

社会与信息网络 · 计算机科学 2019-02-06 Prakhar Ganesh , Saket Dingliwal , Rahul Agarwal

Many real-world networks are so large that we must simplify their structure before we can extract useful information about the systems they represent. As the tools for doing these simplifications proliferate within the network literature,…

物理与社会 · 物理学 2015-05-13 M. Rosvall , D. Axelsson , C. T. Bergstrom

This entry discusses the problem of describing some communities identified in a complex network of interest, in a way allowing to interpret them. We suppose the community structure has already been detected through one of the many methods…

社会与信息网络 · 计算机科学 2018-05-18 Vincent Labatut , Günce Keziban Orman

Community structure is one of the most important features of real networks and reveals the internal organization of the nodes. Many algorithms have been proposed but the crucial issue of testing, i.e. the question of how good an algorithm…

物理与社会 · 物理学 2008-10-30 Andrea Lancichinetti , Santo Fortunato , Filippo Radicchi

Recording an album brings singers, producers, musicians, audio engineers, and many other professions together. We know from the press that a few "super"-producers work with many artists. But how does the large-scale social structure of the…

社会与信息网络 · 计算机科学 2016-11-03 Pascal Budner , Joern Grahl

Community structure is a typical property of many real-world networks, and has become a key to understand the dynamics of the networked systems. In these networks most nodes apparently lie in a community while there often exists a few nodes…

社会与信息网络 · 计算机科学 2017-12-07 Zhan Weihua , Chen Huahui , Guan Jihong , Jin Guang

Networks are representations of complex underlying social processes. However, the same given network may be more suitable to model one behavior of individuals than another. In many cases, aggregate population models may be more effective…

社会与信息网络 · 计算机科学 2017-08-22 Ivan Brugere , Chris Kanich , Tanya Y. Berger-Wolf

In recent years, community structure has emerged as a key component of complex network analysis. As more data has been collected, researchers have begun investigating changing community structure across multiple networks. Several methods…

社会与信息网络 · 计算机科学 2011-08-03 Matthew Steen , Satoru Hayasaka , Karen Joyce , Paul Laurienti