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Detecting global bridges in networks

Authors: Jensen, Pablo; Morini, Matteo; Karsai, Márton; Venturini, Tommaso; Vespignani, Alessandro; Jacomy, Mathieu; Cointet, Jean-Philippe; +2 Authors

Detecting global bridges in networks

Abstract

The identification of nodes occupying important positions in a network structure is crucial for the understanding of the associated real-world system. Usually, betweenness centrality is used to evaluate a node capacity to connect different graph regions. However, we argue here that this measure is not adapted for that task, as it gives equal weight to "local" centers (i.e. nodes of high degree central to a single region) and to "global" bridges, which connect different communities. This distinction is important as the roles of such nodes are different in terms of the local and global organisation of the network structure. In this paper we propose a decomposition of betweenness centrality into two terms, one highlighting the local contributions and the other the global ones. We call the latter bridgeness centrality and show that it is capable to specifically spot out global bridges. In addition, we introduce an effective algorithmic implementation of this measure and demonstrate its capability to identify global bridges in air transportation and scientific collaboration networks.

Journal of Complex Networks Preprint; 14 pages; 6 figures

Countries
Italy, Switzerland, France
Keywords

Bridgeness Centrality, Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, [INFO.INFO-SI] Computer Science [cs]/Social and Information Networks [cs.SI], 305.3, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI], 004, Betweenness Centrality, Betweenness centrality; Bridgeness centrality; Centrality measures; Computer Networks and Communications; Control and Optimization; Management Science and Operations Research; Computational Mathematics; Applied Mathematics, Centrality Measures, ddc: ddc:305.3

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    41
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
41
Top 10%
Top 10%
Top 10%
Green
bronze