Entropy-Based Influence Disseminator (EbID) quantifies node influence by combining an entropy-based node quality index with the community structure of its neighbors [2]. The centrality of node \(i\) is defined as
\begin{equation*}
c_{\text{EbID}}(i) = \sum_{j \in \mathcal{N}(i)} \frac{1}{d_i (d_j - 1)} \log \frac{1}{d_i (d_j - 1)}
+ \sum_{j \in \mathcal{N}(i)} v(C_j),
\end{equation*}
where \(\mathcal{N}(i)\) is the set of neighbors of node \(i\), \(d_i\) is the degree of node \(i\). The first term captures the entropy of the probability distribution of reaching a node in two hops, and the second term, \(v(C_j)\), measures the relative edge density of the community to which node \(j\) belongs. Saxena et al. [2] employ the Louvain method to detect communities.
Nodes with higher \(c_{\text{EbID}}(i)\) are those that not only provide efficient two-hop reachability but also are connected to well-connected communities, making them effective disseminators of influence in the network.

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] Saxena, C., Doja, M. N., & Ahmad, T. (2020). Entropy based flow transfer for influence dissemination in networks. Physica A: Statistical Mechanics and its Applications, 555, 124630. doi: 10.1016/j.physa.2020.124630.