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Comparing community structure identification
- Source :
- Journal of Statistical Mechanics: Theory and Experiment. 2005:P09008-P09008
- Publication Year :
- 2005
- Publisher :
- IOP Publishing, 2005.
-
Abstract
- We compare recent approaches to community structure identification in terms of sensitivity and computational cost. The recently proposed modularity measure is revisited and the performance of the methods as applied to ad hoc networks with known community structure, is compared. We find that the most accurate methods tend to be more computationally expensive, and that both aspects need to be considered when choosing a method for practical purposes. The work is intended as an introduction as well as a proposal for a standard benchmark test of community detection methods.<br />Comment: 10 pages, 3 figures, 1 table. v2: condensed, updated version as appears in JSTAT
- Subjects :
- Statistics and Probability
Physics - Physics and Society
Measure (data warehouse)
Modularity (networks)
business.industry
Wireless ad hoc network
Computer science
Girvan–Newman algorithm
FOS: Physical sciences
Statistical and Nonlinear Physics
Disordered Systems and Neural Networks (cond-mat.dis-nn)
Physics and Society (physics.soc-ph)
Condensed Matter - Disordered Systems and Neural Networks
Machine learning
computer.software_genre
Clique percolation method
Identification (information)
Benchmark (computing)
Artificial intelligence
Sensitivity (control systems)
Statistics, Probability and Uncertainty
business
computer
Subjects
Details
- ISSN :
- 17425468
- Volume :
- 2005
- Database :
- OpenAIRE
- Journal :
- Journal of Statistical Mechanics: Theory and Experiment
- Accession number :
- edsair.doi.dedup.....6c0aee7f3c7b00574a783d61b3fa21ee
- Full Text :
- https://doi.org/10.1088/1742-5468/2005/09/p09008