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communicability_betweenness_centrality¶
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communicability_betweenness_centrality
(G, normalized=True)[source]¶ Return communicability betweenness for all pairs of nodes in G.
Communicability betweenness measure makes use of the number of walks connecting every pair of nodes as the basis of a betweenness centrality measure.
Parameters: G: graph
Returns: nodes:dictionary
Dictionary of nodes with communicability betweenness as the value.
Raises: NetworkXError
If the graph is not undirected and simple.
See also
communicability
- Communicability between all pairs of nodes in G.
communicability_centrality
- Communicability centrality for each node of G using matrix exponential.
communicability_centrality_exp
- Communicability centrality for each node in G using spectral decomposition.
Notes
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 [R177]
ωr=1C∑p∑qGprqGpq,p≠q,q≠r,where Gprq=(eApq−(eA+E(r))pq is the number of walks involving node r, Gpq=(eA)pq is the number of closed walks starting at node p and ending at node q, and C=(n−1)2−(n−1) is a normalization factor equal to the number of terms in the sum.
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.
References
[R177] (1, 2) Ernesto Estrada, Desmond J. Higham, Naomichi Hatano, “Communicability Betweenness in Complex Networks” Physica A 388 (2009) 764-774. http://arxiv.org/abs/0905.4102 Examples
>>> G = nx.Graph([(0,1),(1,2),(1,5),(5,4),(2,4),(2,3),(4,3),(3,6)]) >>> cbc = nx.communicability_betweenness_centrality(G)