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Note

This documents the development version of NetworkX. Documentation for the current release can be found here.

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networkx.algorithms.centrality.dispersion

dispersion(G, u=None, v=None, normalized=True, alpha=1.0, b=0.0, c=0.0)[source]

Calculate dispersion between u and v in G.

A link between two actors (u and v) has a high dispersion when their mutual ties (s and t) are not well connected with each other.

Parameters

  • G (graph) – A NetworkX graph.

  • u (node, optional) – The source for the dispersion score (e.g. ego node of the network).

  • v (node, optional) – The target of the dispersion score if specified.

  • normalized (bool) – If True (default) normalize by the embededness of the nodes (u and v).

Returns

nodes – If u (v) is specified, returns a dictionary of nodes with dispersion score for all “target” (“source”) nodes. If neither u nor v is specified, returns a dictionary of dictionaries for all nodes ‘u’ in the graph with a dispersion score for each node ‘v’.

Return type

dictionary

Notes

This implementation follows Lars Backstrom and Jon Kleinberg 1. Typical usage would be to run dispersion on the ego network \(G_u\) if \(u\) were specified. Running dispersion() with neither \(u\) nor \(v\) specified can take some time to complete.

References

1

Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook. Lars Backstrom, Jon Kleinberg. https://arxiv.org/pdf/1310.6753v1.pdf