Linearly scaled betweenness centrality is a variant of betweenness centrality that weights shortest paths according to the relative position of intermediate nodes along the path from the source [2, 3]. The centrality of node \(i\) is defined as
\begin{equation*}
c_{b-lin}(i) = \sum_{j=1}^{N} \sum_{k=1}^{N} \frac{d_{ji}}{d_{jk}} \frac{σ_{jk}(i)}{σ_{jk}},
\end{equation*}
where \(d_{jk}\) is the length of the shortest path from \(j\) to \(k\), \(σ_{jk}\) is the total number of shortest paths between \(j\) and \(k\), and \(σ_{jk}(i)\) is the number passing through \(i\). Nodes farther from the source, and thus closer to the target, contribute more to centrality. In undirected graphs, however, linearly scaled betweenness reduces to standard betweenness centrality, since the relative distances along paths in opposite directions sum to one:
\[
\frac{d_{ji}}{d_{jk}} + \frac{d_{ki}}{d_{kj}} = 1.
\]

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] Geisberger, R., Sanders, P., & Schultes, D. (2008). Better approximation of betweenness centrality. In 2008 Proceedings of the Tenth Workshop on Algorithm Engineering and Experiments (ALENEX) (pp. 90-100). Society for Industrial and Applied Mathematics. doi: 10.1137/1.9781611972887.9.
[3] Brandes, U. (2008). On variants of shortest-path betweenness centrality and their generic computation. Social networks, 30(2), 136-145. doi: 10.1016/j.socnet.2007.11.001.