Modularity

S��bastien Heymann edited this page Mar 2, 2015 · 2 revisions
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Measures how well a network decomposes into modular communities.

Objective

A high modularity score indicates sophisticated internal structure. This structure, often called a community structure, describes how the the network is compartmentalized into sub-networks. These sub-networks (or communities) have been shown to have significant real-world meaning.

Explanation

Randomizing the algorithm can produce a better decomposition resulting in a higher modularity score, however randomizing will increase computation time.

Source code

See org.gephi.statistics.plugin.Modularity.java.

Acknowledgments

This code was implemented by Patrick McSweeney.

Implemented Algorithm

Vincent D. Blondel, Jean-Loup Guillaume, Renaud Lambiotte, Etienne Lefebvre - Fast unfolding of communities in large networks (2008) PDF

Reference