community detection modularity suite

We have hosted the application community detection modularity suite in order to run this application in our online workstations with Wine or directly.

Quick description about community detection modularity suite:

- MixtureModel_v1r1: overlapping community algorithm [3], which includes novel partition density and fuzzy modularity metrics.

- OpenMP versions of algorithms in [1] are available to download.

- Main suite containing three community detection algorithms based on the Modularity measure containing: Geodesic and Random Walk edge Betweenness [1] and Spectral Modularity [2].


Collaborator: Theologos Kotsos.

[1] M. Newman & M. Girvan, Physical Review, E 69 (026113), 2004.
[2] M. Newman, Physical Review E, 74(3): 036104, 2006.
[3] B. Ball et al, An efficient and principled method for detecting communities in networks, 2011.
The suite is based upon the fast community algorithm implemented by Aaron Clauset <[email protected]>, Chris Moore, Mark Newman, and the R IGraph library Copyright (C) 2007 Gabor Csardi <[email protected]>. It also makes of the classes available from Numerical Recipies 3rd Edition W. Press, S. Teukolsky, W. Vetterling, B. Flanne.

Features:

• C++ and R implementations of Newman & Girvan Modularity based community detection algorithms
• R implementations of the edge Betweenness Random Walk algorithm
• Boot-strapping factilities to test cluster robustness
• Version 2 (v2r1) contains OpenMP implementation of Newman & Girvan Geodesic and Random Walk edge Betweenness algorithms
• Overlapping community detection model, including the partition density and fuzzy modularity metrics for community detection

Audience: Science/Research.
User interface: Console/Terminal.
Programming Language: C++, S/R.
Categories: