Hybrid centrality (X) was proposed by Pozzi et al. [2] to improve the stability and robustness of node rankings by combining classical centrality measures, which are often positively correlated. Specifically, \(X\) aggregates the rankings of degree and betweenness centralities in both unweighted and weighted networks:
\[
X = \frac{c_D^u + c_D^w + c_{BC}^u + c_{BC}^w - 4}{4(N-1)},
\]
where \(c_D\) and \(c_{BC}\) denote the rankings of nodes by degree and betweenness centralities in unweighted (\(u\)) and weighted (\(w\)) networks. Nodes with low \(X\) values are highly central, whereas high values indicate peripheral nodes.

References

[1] Shvydun, S. (2025). Zoo of Centralities: Encyclopedia of Node Metrics in Complex Networks. arXiv: 2511.05122 https://doi.org/10.48550/arXiv.2511.05122
[2] Pozzi, F., Di Matteo, T., & Aste, T. (2013). Spread of risk across financial markets: better to invest in the peripheries. Scientific reports, 3(1), 1665. doi: 10.1038/srep01665.