Abstract
We present an alternative approach to assess centrality in networks which does not rely on traditional indices. The work is based on neighborhood-inclusion, a partial ranking inducing relation of nodes, which was shown to be preserved by many existing centrality indices. As such, it can serve as the shared basis for centrality in networks. We argue that evaluating this partial ranking by itself allows for a generic assessment of centrality, avoiding several pitfalls that can arise when indices are applied. Additionally, we illustrate how to derive further partial rankings and introduce some probabilistic methods to, among others, compute expected centrality ranks of nodes.
Original language | English |
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Pages (from-to) | 50-60 |
Number of pages | 11 |
Journal | Social Networks |
Volume | 54 |
Early online date | 2 Jan 2018 |
DOIs | |
Publication status | Published - 1 Jul 2018 |
Keywords
- Centrality indices
- Partial orders
- Network centrality
- Neighborhood-inclusion
- Rank probabilities