Narrow scope for resolution-limit-free community detection
Vincent Traaga b, Paul M. Van Doorenb, Yurii E. Nesterovb c
- aICTEAM, Université Catholique de Louvain, Louvain-la Neuve, Belgium. vincent.traag@uclouvain.be
- bICTEAM, Université Catholique de Louvain, Bâtiment Euler, Avenue G. Lemaître 4, B-1348 Louvain-la Neuve, Belgium
- cCORE, Université Catholique de Louvain, Voie du Roman Pays 34, B-1348 Louvain-la-Neuve, Belgium
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Abstract
Detecting communities in large networks has drawn much attention over the years. While modularity remains one of the more popular methods of community detection, the so-called resolution limit remains a significant drawback. To overcome this issue, it was recently suggested that instead of comparing the network to a random null model, as is done in modularity, it should be compared to a constant factor. However, it is unclear what is meant exactly by "resolution-limit-free," that is, not suffering from the resolution limit. Furthermore, the question remains what other methods could be classified as resolution-limit-free. In this paper we suggest a rigorous definition and derive some basic properties of resolution-limit-free methods. More importantly, we are able to prove exactly which class of community detection methods are resolution-limit-free. Furthermore, we analyze which methods are not resolution-limit-free, suggesting there is only a limited scope for resolution-limit-free community detection methods. Finally, we provide such a natural formulation, and show it performs superbly.
TL;DRA rigorous definition is suggested and some basic properties of resolution-limit-free methods are derived, able to prove exactly which class of community detection methods are resolution- limit-free, and which methods are not. (Semantic Scholar)