General optimization technique for high-quality community detection in complex networks
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PhysRevE.90.012811.pdf
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466.42 KB
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Author(s)
Sobolevsky, Stanislav
Campari, Riccardo
Belyi, Alexander
Ratti, Carlo
Date Issued
July 2014
Journal
Physical Review E
Publisher
American Physical Society
Citation
Sobolevsky, Stanislav, Riccardo Campari, Alexander Belvi, and Carlo Ratti. "General optimization technique for high-quality community detection in complex networks." Phys. Rev. E 90, 012811 (July 2014). © 2014 American Physical Society
Version
Final published version
Abstract
Recent years have witnessed the development of a large body of algorithms for community detection in complex networks. Most of them are based upon the optimization of objective functions, among which modularity is the most common, though a number of alternatives have been suggested in the scientific literature. We present here an effective general search strategy for the optimization of various objective functions for community detection purposes. When applied to modularity, on both real-world and synthetic networks, our search strategy substantially outperforms the best existing algorithms in terms of final scores of the objective function. In terms of execution time for modularity optimization this approach also outperforms most of the alternatives present in literature with the exception of fastest but usually less efficient greedy algorithms. The networks of up to 30000 nodes can be analyzed in time spans ranging from minutes to a few hours on average workstations, making our approach readily applicable to tasks not limited by strict time constraints but requiring the quality of partitioning to be as high as possible. Some examples are presented in order to demonstrate how this quality could be affected by even relatively small changes in the modularity score stressing the importance of optimization accuracy.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Massachusetts Institute of Technology. SENSEable City Laboratory
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DOI of Published Version
https://doi.org/10.1103/PhysRevE.90.012811
