# Distinctiveness Centrality in Social Networks

arXiv: https://arxiv.org/abs/1912.03391 · HTML: https://mlsanity.com/paper/1912.03391/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Dec 2019.

## Built on by (most cited first, 12 of 12)

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- [Evaluating and improving social awareness of energy communities through semantic network analysis of online news](https://mlsanity.com/paper/2208.01892/) (2022)
- [Informed Machine Learning, Centrality, CNN, Relevant Document Detection, Repatriation of Indigenous Human Remains](https://mlsanity.com/paper/2303.14475/) (2023)
- [Brand Network Booster: A new system for improving brand connectivity](https://mlsanity.com/paper/2309.16228/) (2023)
- [LCA and energy efficiency in buildings: mapping more than twenty years of research](https://mlsanity.com/paper/2409.00065/) (2024)
- [The role of media memorability in facilitating startups' access to venture capital funding](https://mlsanity.com/paper/2507.22201/) (2025)

## Abstract (arXiv)

The determination of node centrality is a fundamental topic in social network studies. As an addition to established metrics, which identify central nodes based on their brokerage power, the number and weight of their connections, and the ability to quickly reach all other nodes, we introduce five new measures of Distinctiveness Centrality. These new metrics attribute a higher score to nodes keeping a connection with the network periphery. They penalize links to highly-connected nodes and serve the identification of social actors with more distinctive network ties. We discuss some possible applications and properties of these newly introduced metrics, such as their upper and lower bounds. Distinctiveness centrality provides a viewpoint of centrality alternative to that of established metrics.
