Overlapping Community Detection in Networks: the State of the Art and Comparative Study
Rensselaer Polytechnic Institute · Oak Ridge National Laboratory
Abstract
This paper 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 over-detection and under-detection. 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…
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Authors
3Topics & keywords
- Computer science
- Node (physics)
- Fraction (chemistry)
- State (computer science)
- Feature (linguistics)
- Data mining
- Community structure
- Machine learning