robins_alexander_clustering¶

robins_alexander_clustering(G)[source]¶

Compute the bipartite clustering of G.

Robins and Alexander [R160] defined bipartite clustering coefficient as four times the number of four cycles \(C_4\) divided by the number of three paths \(L_3\) in a bipartite graph:

\[CC_4 = \frac{4 * C_4}{L_3}\]

Parameters :	G : graph a bipartite graph
Returns :	clustering : float The Robins and Alexander bipartite clustering for the input graph.

See also

latapy_clustering, square_clustering

References

[R160]

(1, 2) Robins, G. and M. Alexander (2004). Small worlds among interlocking directors: Network structure and distance in bipartite graphs. Computational & Mathematical Organization Theory 10(1), 69–94.

Examples

>>> from networkx.algorithms import bipartite
>>> G = nx.davis_southern_women_graph()
>>> print(round(bipartite.robins_alexander_clustering(G), 3))
0.468