# A Survey on Centrality Metrics and Their Implications in Network Resilience

arXiv: https://arxiv.org/abs/2011.14575 · HTML: https://mlsanity.com/paper/2011.14575/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Nov 2020.

## Built on by (most cited first, 3 of 3)

- [Opinion Leader Detection in Online Social Networks Based on Output and Input Links](https://mlsanity.com/paper/2208.13161/) (2022)
- [Using Graph Theory for Improving Machine Learning-based Detection of Cyber Attacks](https://mlsanity.com/paper/2402.07878/) (2024)
- [SNAP: A Self-Consistent Agreement Principle with Application to Robust Computation](https://mlsanity.com/paper/2602.02013/) (2026)

## Abstract (arXiv)

Centrality metrics have been used in various networks, such as communication, social, biological, geographic, or contact networks. In particular, they have been used in order to study and analyze targeted attack behaviors and investigated their effect on network resilience. Although a rich volume of centrality metrics has been developed for decades, a limited set of centrality metrics have been commonly in use. This paper aims to introduce various existing centrality metrics and discuss their applicabilities and performance based on the results obtained from extensive simulation experiments to encourage their use in solving various computing and engineering problems in networks.