English

A Centrality Measure Using Magnitude Homology

Algebraic Topology 2026-07-17 v1 Social and Information Networks

Abstract

The magnitude of a metric space constitutes an expressive invariant that subsumes numerous different geometrical-topological invariants. Building on recent advances in magnitude homology, i.e., a bigraded homology theory that recovers the magnitude, we develop a novel local measure of the centrality or importance of nodes in a graph. Our measure is inspired by the concept of relative homology as it considers the change in magnitude homology when removing a vertex. We show that our proposed measure satisfies several properties a centrality measure is reasonably expected to respect and demonstrate that we introduce a new perspective on centrality by comparing to several established centrality measures.

Keywords

Cite

@article{arxiv.2607.16377,
  title  = {A Centrality Measure Using Magnitude Homology},
  author = {Nadja Häusermann and Bastian Rieck},
  journal= {arXiv preprint arXiv:2607.16377},
  year   = {2026}
}