Towards Classifying the Polynomial-Time Solvability of Temporal Betweenness Centrality

Maciej Rymar, Hendrik Molter, André Nichterlein, Rolf Niedermeier

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

In static graphs, the betweenness centrality of a graph vertex measures how many times this vertex is part of a shortest path between any two graph vertices. Betweenness centrality is efficiently computable and it is a fundamental tool in network science. Continuing and extending previous work, we study the efficient computability of betweenness centrality in temporal graphs (graphs with fixed vertex set but time-varying arc sets). Unlike in the static case, there are numerous natural notions of being a “shortest” temporal path (walk). Depending on which notion is used, it was already observed that the problem is #P-hard in some cases while polynomial-time solvable in others. In this conceptual work, we contribute towards classifying what a “shortest path (walk) concept” has to fulfill in order to gain polynomial-time computability of temporal betweenness centrality.

Original languageEnglish
Title of host publicationGraph-Theoretic Concepts in Computer Science - 47th International Workshop, WG 2021, Revised Selected Papers
EditorsLukasz Kowalik, Michal Pilipczuk, Pawel Rzazewski
PublisherSpringer Science and Business Media Deutschland GmbH
Pages219-231
Number of pages13
ISBN (Print)9783030868376
DOIs
StatePublished - 1 Jan 2021
Event47th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2021 - Virtual, Online
Duration: 23 Jun 202125 Jun 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12911 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference47th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2021
CityVirtual, Online
Period23/06/2125/06/21

Keywords

  • Counting complexity
  • Network centrality measures
  • Network science
  • Temporal graphs
  • Temporal paths and walks

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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