Journal ArticleDOI
Second order centrality: Distributed assessment of nodes criticity in complex networks
TLDR
A novel form of centrality is introduced: the second order centrality which can be computed in a distributed manner which provides locally each node with a value reflecting its relative criticity and relies on a random walk visiting the network in an unbiased fashion.About:
This article is published in Computer Communications.The article was published on 2011-04-01. It has received 89 citations till now. The article focuses on the topics: Random walk closeness centrality & Katz centrality.read more
Citations
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Journal ArticleDOI
Betweenness Centrality in Large Complex Networks
TL;DR: In this article, the authors analyzed the betweenness centrality of nodes in large complex networks and showed that for trees or networks with a small loop density, a larger density of loops leads to the same result.
Journal ArticleDOI
Identifying node importance based on evidence theory in complex networks
Hongming Mo,Yong Deng +1 more
TL;DR: A new multi-evidence centrality is proposed based on evidence theory, taking into consideration the existing measures of degree centrality, betweennesscentrality, efficiency centrality and correlation centrality into consideration.
Journal ArticleDOI
Identifying node importance in complex networks
TL;DR: The cascading failures on the Netscience and E-mail networks demonstrate that the networks are more vulnerable when continuously removing the important nodes identified by the method, which further proves the accuracy of the method.
Journal ArticleDOI
DACCER: Distributed Assessment of the Closeness CEntrality Ranking in complex networks
Klaus Wehmuth,Artur Ziviani +1 more
TL;DR: DACCER is simple, yet efficient, in assessing node centrality while allowing a distributed implementation that contributes to its performance, which contributes to the practical applicability of DACCER to the analysis of large complex networks.
Proceedings ArticleDOI
Distributed assessment of the closeness centrality ranking in complex networks
Klaus Wehmuth,Artur Ziviani +1 more
TL;DR: It is shown that the node centrality ranking computed by DACCER is highly correlated with the node ranking based on the traditional closeness centrality, which requires high computational costs and full knowledge of the network topology.
References
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Journal ArticleDOI
Statistical mechanics of complex networks
TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
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Monte Carlo Sampling Methods Using Markov Chains and Their Applications
TL;DR: A generalization of the sampling method introduced by Metropolis et al. as mentioned in this paper is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates.
Proceedings Article
The PageRank Citation Ranking : Bringing Order to the Web
TL;DR: This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them, and shows how to efficiently compute PageRank for large numbers of pages.
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A Set of Measures of Centrality Based on Betweenness
TL;DR: A family of new measures of point and graph centrality based on early intuitions of Bavelas (1948) is introduced in this paper, which define centrality in terms of the degree to which a point falls on the shortest path between others and there fore has a potential for control of communication.
Journal ArticleDOI
Error and attack tolerance of complex networks
TL;DR: It is found that scale-free networks, which include the World-Wide Web, the Internet, social networks and cells, display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected even by unrealistically high failure rates.