Finding groups with maximum betweenness centrality

DOI10.1080/10556788.2016.1167892zbMath1365.05269OpenAlexW2346326891MaRDI QIDQ5268927

Oleg A. Prokopyev, Eduardo L. Pasiliao, Alexander Veremyev

Publication date: 21 June 2017

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10556788.2016.1167892

zbMATH Keywords

mixed integer programmingbetweenness centralitybounded-distance betweenness centralitygroup betweenness centralitymost central groups

Mathematics Subject Classification ID

Small world graphs, complex networks (graph-theoretic aspects) (05C82) Integer programming (90C10) Deterministic network models in operations research (90B10)

Related Items (7)

The Star Degree Centrality Problem: A Decomposition Approach ⋮ Novel centrality metrics for studying essentiality in protein‐protein interaction networks based on group structures ⋮ Finding the most degree-central walks and paths in a graph: exact and heuristic approaches ⋮ Finding groups with maximum betweenness centrality via integer programming with random path sampling ⋮ On exact solution approaches for the longest induced path problem ⋮ Finding clique clusters with the highest betweenness centrality ⋮ Detecting a most closeness-central clique in complex networks

Uses Software

• Pajek datasets
• SparseMatrix
• XPRESS
• DIMACS

Cites Work

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• Finding maximum subgraphs with relatively large vertex connectivity
• Identifying large robust network clusters via new compact formulations of maximum \(k\)-club problems
• Incremental deployment of network monitors based on Group Betweenness Centrality
• On the maximum quasi-clique problem
• On clique relaxation models in network analysis
• An integer programming approach for finding the most and the least central cliques
• A faster algorithm for betweenness centrality*
• Clique Relaxations in Social Network Analysis: The Maximum k-Plex Problem
• Statistical mechanics of complex networks
• Maximum Betweenness Centrality: Approximability and Tractable Cases
• Emergence of Scaling in Random Networks
• The centrality of groups and classes
• Community structure in social and biological networks
• Collective dynamics of ‘small-world’ networks
• Networks

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