Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1103/PhysRevE.84.016114 | PHYSICAL REVIEW E |
Field | DocType | Volume |
Computer science,Remote sensing | Journal | 84 |
Issue | ISSN | Citations |
1 | 1539-3755 | 4 |
PageRank | References | Authors |
0.44 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vincent A. Traag | 1 | 107 | 9.04 |
| Paul van Dooren | 2 | 649 | 90.48 |
| Yurii Nesterov | 3 | 1800 | 168.77 |