Quality functions in community detection
arXiv:0705.4445 · doi:10.1117/12.726703
Abstract
Community structure represents the local organization of complex networks and the single most important feature to extract functional relationships between nodes. In the last years, the problem of community detection has been reformulated in terms of the optimization of a function, the Newman-Girvan modularity, that is supposed to express the quality of the partitions of a network into communities. Starting from a recent critical survey on modularity optimization, pointing out the existence of a resolution limit that poses severe limits to its applicability, we discuss the general issue of the use of quality functions in community detection. Our main conclusion is that quality functions are useful to compare partitions with the same number of modules, whereas the comparison of partitions with different numbers of modules is not straightforward and may lead to ambiguities.
10 pages, 4 figures, invited paper to appear in the Proceedings of SPIE International Conference "Fluctuations and Noise 2007", Florence, Italy, 20-24 May, 2007
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