Warning

This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.

# betweenness_centrality¶

betweenness_centrality(G, nodes)[source]

Compute betweenness centrality for nodes in a bipartite network.

Betweenness centrality of a node $$v$$ is the sum of the fraction of all-pairs shortest paths that pass through $$v$$.

Values of betweenness are normalized by the maximum possible value which for bipartite graphs is limited by the relative size of the two node sets [1].

Let $$n$$ be the number of nodes in the node set $$U$$ and $$m$$ be the number of nodes in the node set $$V$$, then nodes in $$U$$ are normalized by dividing by

$\frac{1}{2} [m^2 (s + 1)^2 + m (s + 1)(2t - s - 1) - t (2s - t + 3)] ,$

where

$s = (n - 1) \div m , t = (n - 1) \mod m ,$

and nodes in $$V$$ are normalized by dividing by

$\frac{1}{2} [n^2 (p + 1)^2 + n (p + 1)(2r - p - 1) - r (2p - r + 3)] ,$

where,

$p = (m - 1) \div n , r = (m - 1) \mod n .$
Parameters: G (graph) – A bipartite graph nodes (list or container) – Container with all nodes in one bipartite node set. betweenness – Dictionary keyed by node with bipartite betweenness centrality as the value. dictionary

degree_centrality(), closeness_centrality(), sets(), is_bipartite()