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Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms

# Subcubic Equivalences Between Graph Centrality Problems, APSP and Diameter

## Abstract

Measuring the importance of a node in a network is a major goal in the analysis of social networks, biological systems, transportation networks etc. Different centrality measures have been proposed to capture the notion of node importance. For example, the center of a graph is a node that minimizes the maximum distance to any other node (the latter distance is the radius of the graph). The median of a graph is a node that minimizes the sum of the distances to all other nodes. Informally, the betweenness centrality of a node w measures the fraction of shortest paths that have w as an intermediate node. Finally, the reach centrality of a node w is the smallest distance r such that any s-t shortest path passing through w has either s or t in the ball of radius r around w.
The fastest known algorithms to compute the center and the median of a graph, and to compute the betweenness or reach centrality even of a single node take roughly cubic time in the number n of nodes in the input graph. It is open whether these problems admit truly subcubic algorithms, i.e. algorithms with running time Õ(n3–δ) for some constant δ > 01.
We relate the complexity of the mentioned centrality problems to two classical problems for which no truly subcubic algorithm is known, namely All Pairs Shortest Paths (APSP) and Diameter. We show that Radius, Median and Betweenness Centrality are equivalent under subcubic reductions to APSP, i.e. that a truly subcubic algorithm for any of these problems implies a truly subcubic algorithm for all of them. We then show that Reach Centrality is equivalent to Diameter under subcubic reductions. The same holds for the problem of approximating Betweenness Centrality within any constant factor. Thus the latter two centrality problems could potentially be solved in truly subcubic time, even if APSP requires essentially cubic time.

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### Information

#### Published In

Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms
Pages: 1681 - 1697
Editor: Piotr Indyk, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
ISBN (Print): 978-1-61197-374-7
ISBN (Online): 978-1-61197-373-0

#### History

Published online: 22 December 2014

### Authors

#### Affiliations

Virginia Vassilevska Williams

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