Journal of Graph Algorithms and Applications
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Computing Betweenness Centrality in Link Streams
Frédéric Simard, Clémence Magnien, and Matthieu Latapy
Vol. 27, no. 3, pp. 195-217, 2023. Regular paper.
Abstract Betweeness centrality is one of the most important concepts in graph analysis. It was recently extended to link streams, a graph generalization where links arrive over time. However, its computation raises non-trivial issues, due in particular to the fact that time is considered as continuous. We provide here the first algorithms to compute this generalized betweenness centrality, as well as several companion algorithms that have their own interest. They work in polynomial time and space, we illustrate them on typical examples, and we provide an implementation.
This work is licensed under the terms of the CC-BY license.
Submitted: February 2021.
Reviewed: March 2022.
Revised: June 2022.
Accepted: February 2023.
Final: March 2023.
Published: May 2023.
Communicated by Ulrik Brandes