robins_alexander_clustering¶

robins_alexander_clustering(G)[source]¶

Compute the bipartite clustering of G.

Robins and Alexander [1] 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 – The Robins and Alexander bipartite clustering for the input graph.
Return type:	float

Examples

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

See also

latapy_clustering(), square_clustering()

References

[1]	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.