The k -shell based on gravity centrality (KSGC) is an extension of the local gravity model that integrates both \(k\)-shell and degree centralities to identify influential nodes in complex networks [2].
Let \(\mathcal{N}^{(\leq k)}(i)\) denote set of nodes within the \(k\)-hop neighbourhood of node \(i\). The centrality \( c_{\textsc{KSGC}}(i) \) of node \( i \) is defined as
\begin{equation*}
c_{\textsc{KSGC}}(i) =
\sum_{j \in \mathcal{N}^{(\leq k)}(i)}
e^{\frac{k_s(i) - k_s(j)}{ks_{\max} - ks_{\min}}}
\cdot
\frac{d_i d_j}{d_{ij}^2},
\end{equation*}
where \( d_{ij} \) is the shortest-path distance between nodes \( i \) and \( j \), \( d_i \) is the degree of node \( i \) and \( k_s(i) \) is the \(k\)-shell index of node \( i \). The terms \( ks_{\max} \) and \( ks_{\min} \) represent the maximum and minimum \(k\)-shell values in the network, respectively. Yang and Xiao [2] consider \( l = 2 \) as the truncated radius.

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] Yang, X., & Xiao, F. (2021). An improved gravity model to identify influential nodes in complex networks based on k-shell method. Knowledge-Based Systems, 227, 107198. doi: 10.1016/j.knosys.2021.107198.