Overlapping community detection in networks
Rensselaer Polytechnic Institute · Oak Ridge National Laboratory
Abstract
This article reviews the state-of-the-art in overlapping community detection algorithms, quality measures, and benchmarks. A thorough comparison of different algorithms (a total of fourteen) is provided. In addition to community-level evaluation, we propose a framework for evaluating algorithms' ability to detect overlapping nodes, which helps to assess overdetection and underdetection. After considering community-level detection performance measured by normalized mutual information, the Omega index, and node-level detection performance measured by F-score, we reached the following conclusions. For low overlapping density networks, SLPA, OSLOM, Game, and COPRA offer better performance than the other tested…
Citation impact
- FWCI
- 56.17
- Percentile
- 100%
- References
- 117
Authors
3Topics & keywords
- Computer science
- Fraction (chemistry)
- Node (physics)
- Feature (linguistics)
- Artificial intelligence
- Machine learning
- Data mining