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Poster communications

Bridgeness: a novel centrality measure to detect global bridges

Abstract : Finding nodes occupying interesting positions in a graph is useful to extract meaningful information from large datasets. While numerous measures have been proposed to evaluate the centrality of nodes, few indicators quantify the capacity of nodes to connect different regions of the graph. Usually, betweenness centrality is used for this purpose, but we show here that it gives equal scores to “local” centers (i.e. nodes of high degree central to a single region) and to “global” bridges, which connect different regions. This distinction is important because the roles of these nodes are quite diverse. For example, in networks of scientific collaborations, local centers correspond to nodes which are important for a single sub-discipline, while bridges correspond to nodes which connect different sub-disciplines, leading to interdisciplinary collaborations. We show that a new measure of network topology, the bridgeness, is able to discriminate between local centers and global bridges, in synthetic and real networks.
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Poster communications
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Contributor : Matteo Morini Connect in order to contact the contributor
Submitted on : Saturday, July 11, 2015 - 8:04:53 PM
Last modification on : Wednesday, November 3, 2021 - 3:41:12 PM
Long-term archiving on: : Monday, October 12, 2015 - 11:40:02 AM


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Distributed under a Creative Commons Attribution 4.0 International License


  • HAL Id : hal-01175702, version 1


Pablo Jensen, Matteo Morini, Tommaso Venturini, Mathieu Jacomy, Jean-Philippe Cointet, et al.. Bridgeness: a novel centrality measure to detect global bridges. ECCS 2014 – European Conference on Complex Systems, Sep 2014, Lucca, Italy. 2014. ⟨hal-01175702⟩



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