Measures how well a network decomposes into modular communities.
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.
Randomizing the algorithm can produce a better decomposition resulting in a higher modularity score, however randomizing will increase computation time.
This code was implemented by Patrick McSweeney.
Vincent D. Blondel, Jean-Loup Guillaume, Renaud Lambiotte, Etienne Lefebvre - Fast unfolding of communities in large networks (2008) PDF