Axiomatic characterization of game-theoretic network centralities

Oskar Skibski, Tomasz P. Michalak, Talal Rahwan

Research output: Contribution to conferencePaper

Abstract

One of the fundamental research challenges in network science is the centrality analysis, i.e., identifying the nodes that play the most important roles in the network. In this paper, we focus on the game-theoretic approach to centrality analysis. While various centrality indices have been proposed based on this approach, it is still unknown what distinguishes this family of indices from the more classical ones. In this paper, we answer this question by providing the first axiomatic characterization of game-theoretic centralities. Specifically, we show that every centrality can be obtained following the game-theoretic approach, and show that two natural classes of game-theoretic centrality can be characterized by two intuitive properties pertaining to Myerson's notion of Fairness.

Original languageEnglish (US)
Pages698-705
Number of pages8
Publication statusPublished - Jan 1 2017
Event31st AAAI Conference on Artificial Intelligence, AAAI 2017 - San Francisco, United States
Duration: Feb 4 2017Feb 10 2017

Other

Other31st AAAI Conference on Artificial Intelligence, AAAI 2017
CountryUnited States
CitySan Francisco
Period2/4/172/10/17

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Skibski, O., Michalak, T. P., & Rahwan, T. (2017). Axiomatic characterization of game-theoretic network centralities. 698-705. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.