# Towards Classifying the Polynomial-Time Solvability of Temporal Betweenness Centrality

@article{Rymar2021TowardsCT, title={Towards Classifying the Polynomial-Time Solvability of Temporal Betweenness Centrality}, author={Maciej Rymar and Hendrik Molter and Andr{\'e} Nichterlein and Rolf Niedermeier}, journal={ArXiv}, year={2021}, volume={abs/2105.13055} }

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…

## 3 Citations

Temporal Connectivity: Coping with Foreseen and Unforeseen Delays

- Computer ScienceSAND
- 2022

This work gives polynomial-time algorithms for the two extreme cases: delays known before departure and delays occurring without prior warning (the latter leading to a two-player game scenario).

ONBRA: Rigorous Estimation of the Temporal Betweenness Centrality in Temporal Networks

- Computer ScienceWWW
- 2022

This work presents, the first sampling-based approximation algorithm for estimating the temporal betweenness centrality values of the nodes in a temporal network, providing rigorous probabilistic guarantees on the quality of its output.

Counting Temporal Paths

- Computer Science
- 2022

This work initiates a systematic study of the prameterised and approximation complexity of #Temporal Path, the problem of counting all temporal paths between a fixed pair of vertices; like the problems of counting foremost and fastest temporal paths, it is #P-hard in general.

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