Communicability Betweenness Centrality
Let G=(V,E) be a simple undirected graph with n nodes and m edges, and A denote the adjacency matrix of G.
Let G(r)=(V,E(r)) be the graph resulting from removing all edges connected to node r but not the node itself.
The adjacency matrix for G(r) is A+E(r), where E(r) has nonzeros only in row and column r.
The communicability betweenness of a node r is:
The resulting ωr takes values between zero and one. The lower bound cannot be attained for a connected graph, and the upper bound is attained in the star graph.
- A HAGBERG, D. S., P SWART. Exploring Network Structure, Dynamics, and Function using NetworkX. In: G VAROQUAUX, T. V., J MILLMAN, ed. Proceedings of the 7th Python in Science conference (SciPy 2008), 2008. 11-15.
- ESTRADA, E., HIGHAM, D. J. & HATANO, N. 2009. Communicability betweenness in complex networks. Physica A: Statistical Mechanics and its Applications, 388, 764-774. DOI: 10.1016/j.physa.2008.11.011
I know your explanation for the mathematical definition of this measure starts with "Let G=(V,E) be a simple undirected graph...", nevertheless I would like to ask if this centrality measure, along with your algorithm ("communibet" in package centiserve) can be used in directed weighted networks.
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