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An Approximate Flow Betweenness Centrality Measure for Complex Network

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TLDR
This Letter proposes an approximate method to calculate the flow betweenness centrality and provides experimental results as evidence.
Abstract
In complex network analysis, there are various measures to characterize the centrality of each node within a graph, which determines the relative importance of each node. The more centrality a node has in a network, the more significance it has in the spread of infection. As one of the important extensions to shortest-path based betweenness centrality, the flow betweenness centrality is defined as the degree to which each node contributes to the sum of maximum flows between all pairs of nodes. One of the drawbacks of the flow betweenness centrality is that its time complexity is somewhat high. This Letter proposes an approximate method to calculate the flow betweenness centrality and provides experimental results as evidence. key words: complex network, centrality, flow betweenness centrality, approximate flow betweenness centrality

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The effects of buildings' physical characteristics on urban network centrality

TL;DR: In this article , the authors quantify the buildings' weights by establishing an urban centrality model that includes the building's physical characteristics and positions, and demonstrate that buildings' architectural traits influence urban centralities; the effect is negative when enhanced by implicit spatial network anti-betweenness, explaining that such sites are less accessible to the public and unfit for future growth.
Journal ArticleDOI

Assessment of flow paths and confluences for saltwater intrusion in a deltaic river network

TL;DR: In this paper, a centrality index, the betweenness centrality (BC), is introduced to detect the major flow paths or locations at risk of saltwater intrusion in estuarine ecosystems.
Journal ArticleDOI

Emergency Repair Scope Partition of City Water Distribution Network: a Novel Approach Considering the Node Importance

TL;DR: A graph-theoretic and multi-objective approach for the partition of CWDN that can finish the emergency repair scope partition quickly and easily since it does not rely on precise hydraulic simulation which requires complex calibration processes and computation, while remaining meaningful from a physical and topological point of view.
Journal ArticleDOI

Traffic Inequality and Relations in Maritime Silk Road: A Network Flow Analysis

TL;DR: Based on the AIS (Automatic Identification System) trajectory data of ships, the authors constructs the Maritime Silk Road traffic network and empirically demonstrate the traffic inequality in the route, and explore the role of the country in the maritime traffic system and the resulting traffic relations.
Book ChapterDOI

A Method of Node Importance Measurement Base on Community Structure in Heterogeneous Combat Networks

TL;DR: In this paper, the authors propose an evaluation model based on community structure, which can measure the importance of each node, and compare it with traditional ranking models (e.g., degree centrality).
References
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Journal ArticleDOI

Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
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Emergence of Scaling in Random Networks

TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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Centrality in social networks conceptual clarification

TL;DR: In this article, three distinct intuitive notions of centrality are uncovered and existing measures are refined to embody these conceptions, and the implications of these measures for the experimental study of small groups are examined.
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A faster algorithm for betweenness centrality

TL;DR: New algorithms for betweenness are introduced in this paper and require O(n + m) space and run in O(nm) and O( nm + n2 log n) time on unweighted and weighted networks, respectively, where m is the number of links.
Journal ArticleDOI

A measure of betweenness centrality based on random walks

TL;DR: In this paper, the authors propose a measure of betweenness based on random walks, counting how often a node is traversed by a random walk between two other nodes, not just the shortest paths.