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Approximation of Interactive Betweenness Centrality in Large Complex Networks
Complexity, 2020 The analysis of real-world systems through the lens of complex networks often requires a node importance function. While many such views on importance exist, a frequently used global node importance measure is betweenness centrality, quantifying the ...
Sebastian Wandelt +2 more
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Interoperability between central counterparties [PDF]
The Journal of Financial Market Infrastructures, 2015 In reaction to recent requests for interoperability between central counterparties of European stock markets, regulators have issued new guidelines to contain systemic risk. Our analysis confirms that the currently applied cross-CCP risk management model can be a source of contagion, particularly if applied in multilateral frameworks. While regulators'
Jürg Mägerle, Thomas Nellen
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Promet (Zagreb), 2022 The centrality of stations is one of the most important issues in urban transit systems. The central stations of such networks have often been identified using network to-pological centrality measures.
Ruiyong Tong +4 more
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Relative edge betweenness centrality
Ars Mathematica Contemporanea, 2016 We introduce a new edge centrality measure - relative edge betweenness γ(uv) = b(uv) / √(c(u)c(v)), where b(uv) is the standard edge betweenness and c(u) is the adjusted vertex betweenness. In this alternative definition, the importance of an edge is normalized with respect to the importance of its end-vertices. This gives a better presentation of the “
Škrekovski, Riste +2 more
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Accelerating GPU betweenness centrality [PDF]
Communications of the ACM, 2018 Graphs that model social networks, numerical simulations, and the structure of the Internet are enormous and cannot be manually inspected. A popular metric used to analyze these networks is Betweenness Centrality (BC), which has applications in community detection, power grid contingency analysis, and the study of the human brain.
McLaughlin, Adam, Bader, David A
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Fast computing betweenness centrality with virtual nodes on large sparse networks. [PDF]
PLoS ONE, 2011 Betweenness centrality is an essential index for analysis of complex networks. However, the calculation of betweenness centrality is quite time-consuming and the fastest known algorithm uses O(N(M + N log N)) time and O(N + M) space for weighted networks,
Jing Yang, Yingwu Chen
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Centrality Learning: Auralization and Route Fitting
Entropy, 2023 Developing a tailor-made centrality measure for a given task requires domain- and network-analysis expertise, as well as time and effort. Thus, automatically learning arbitrary centrality measures for providing ground-truth node scores is an important ...
Xin Li, Liav Bachar, Rami Puzis
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Betweenness Centrality of Fractal and Non-Fractal Scale-Free Model Networks and Tests on Real Networks [PDF]
, 2007 We study the betweenness centrality of fractal and non-fractal scale-free network models as well as real networks. We show that the correlation between degree and betweenness centrality $C$ of nodes is much weaker in fractal network models compared to ...
Havlin, Shlomo +5 more
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Betweenness Centrality – Incremental and Faster [PDF]
, 2014 We consider the incremental computation of the betweenness centrality of all vertices in a large complex network modeled as a graph G = (V, E), directed or undirected, with positive real edge-weights. The current widely used algorithm to compute the betweenness centrality of all vertices in G is the Brandes algorithm that runs in O(mn + n^2 log n) time,
Nasre, Meghana +2 more
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Alpha Current Flow Betweenness Centrality [PDF]
, 2013 A class of centrality measures called betweenness centralities reflects degree of participation of edges or nodes in communication between different parts of the network. The original shortest-path betweenness centrality is based on counting shortest paths which go through a node or an edge.
Avrachenkov, Konstantin +3 more
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