communicability_betweenness_centrality¶

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 of nodes with communicability betweenness as the value. Return type: dictionary 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 be a simple undirected graph with nodes and edges, and denote the adjacency matrix of .
Let be the graph resulting from removing all edges connected to node but not the node itself.
The adjacency matrix for is , where has nonzeros only in row and column .
The communicability betweenness of a node is [1]
where is the number of walks involving node r, is the number of closed walks starting at node and ending at node , and is a normalization factor equal to the number of terms in the sum.
The resulting 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
[1] Ernesto Estrada, Desmond J. Higham, Naomichi Hatano, “Communicability Betweenness in Complex Networks” Physica A 388 (2009) 764774. 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)