Axioms for Distance-Based Centralities

Abstract

We study the class of distance-based centralities that consists of centrality measures that depend solely on distances to other nodes in the graph. This class encompasses a number of centrality measures, including the classical Degree and Closeness Centralities, as well as their extensions: the Harmonic, Reach and Decay Centralities. We axiomatize the class of distance-based centralities and study what conditions are imposed by the axioms proposed in the literature. Building upon our analysis, we propose the class of additive distance-based centralities and pin-point properties which combined with the axiomatic characterization of the whole class uniquely characterize a number of centralities from the literature.

Cite

Text

Skibski and Sosnowska. "Axioms for Distance-Based Centralities." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.11441

Markdown

[Skibski and Sosnowska. "Axioms for Distance-Based Centralities." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/skibski2018aaai-axioms/) doi:10.1609/AAAI.V32I1.11441

BibTeX

@inproceedings{skibski2018aaai-axioms,
  title     = {{Axioms for Distance-Based Centralities}},
  author    = {Skibski, Oskar and Sosnowska, Jadwiga},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {1218-1225},
  doi       = {10.1609/AAAI.V32I1.11441},
  url       = {https://mlanthology.org/aaai/2018/skibski2018aaai-axioms/}
}