K-step betweenness centrality

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2019

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Akgün, Melda Kevser

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The notions of betweenness centrality (BC) and its extension group betweenness centrality (GBC) are widely used in social network analyses. We introduce variants of them; namely, the k-step BC and k-step GBC. The k-step GBC of a group of vertices in a network is a measure of the likelihood that at least one group member will get the information communicated between a randomly chosen pair of vertices through a randomly chosen shortest path within the first k steps of the start of the communication. The k-step GBC of a single vertex is the k-step BC of that vertex. The introduced centrality measures may find uses in applications where it is important or critical to obtain the information within a fixed time of the start of the communication. For the introduced centrality measures, we propose an algorithm that can compute successively the k-step GBC of several groups of vertices. Moreover, we propose a mixed integer programming formulation to compute the group that has the highest k-step GBC value and a heuristic approach to compute a group of vertices whose k-step GBC value is high. The performances of the proposed algorithms are evaluated through computational experiments on real and randomly generated networks.

Subject Keywords

Computer algorithms., Keywords: Betweenness centrality, Group betweenness, Network analysis, Social networks, k-step betweenness.

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http://etd.lib.metu.edu.tr/upload/12623902/index.pdf
https://hdl.handle.net/11511/44039

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

M. K. Akgün, “K-step betweenness centrality,” Thesis (M.S.) -- Graduate School of Natural and Applied Sciences. Industrial Engineering., Middle East Technical University, 2019.