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The merging process is stopped either by setting the expected number of clusters, or by bounding the maximal cluster's cardinality or by maximizing the modularity.
By maximizing the modularity criterion, four communities were identified in this graph.
Specifically, the implement tool "netcarto-w" [ 57] is used to detect modules by maximizing the modularity of the objective network.
We first present detailed numerical results to show the difference of network partition determined by maximizing the modularity density D and modularity Q with simulated annealing (SA) technique.
Communities, or modules, of nodes within the network can be identified by maximizing the modularity, a measure of strength of division of a network into modules [ 14].
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Following this, the nodes were clustered by maximizing the global modularity of the network (Csardi and Nepusz, 2006).
The communities were identified using the network-theoretical community detection algorithm for maximizing the modularity.
In the merging process, subgroup pairs are iteratively merged to identify the final community structure maximizing the modularity.
Thus, maximizing the modularity implies finding the ground-state of this model, and the authors developed a simulated annealing based procedure for doing it.
The "leading eigenvector method" of [15] is able to divide the network in two (or if applied recursively, more) non-overlapping communities maximizing the modularity measure Q.
In those games, we have also exported the topology of each component of the underlying intratype interaction network and applied the Girvan-Newman algorithmaximizingng the modularity to identify the different communities.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com