Fuzzy overlapping communities in networks

Abstract

Networks commonly exhibit a community structure, whereby groups of vertices are more densely connected to each other than to other vertices. Often these communities overlap, such that each vertex may occur in more than one community. However, two distinct types of overlapping are possible: crisp (where each vertex belongs fully to each community of which it is a member) and fuzzy (where each vertex belongs to each community to a different extent). We investigate the effects of the fuzziness of community overlap. We find that it has a strong effect on the performance of community detection methods: some algorithms perform better with fuzzy overlapping while others favour crisp overlapping. We also evaluate the performance of some algorithms that recover the belonging coefficients when the overlap is fuzzy. Finally, we investigate whether real networks contain fuzzy or crisp overlapping.

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Cited by in corpus (11)

• Overlapping Community Detection in Networks: the State of the Art and Comparative Study
• Overlapping Community Detection in Complex Networks using Symmetric Binary Matrix Factorization
• Map equation for link community
• Universality of Performance Indicators based on Citation and Reference Counts
• GenPerm: A Unified Method for Detecting Non-overlapping and Overlapping Communities
• Leveraging disjoint communities for detecting overlapping community structure
• Extension of Modularity Density for Overlapping Community Structure
• Identifying Overlapping and Hierarchical Thematic Structures in Networks of Scholarly Papers: A Comparison of Three Approaches
• Fuzzy Overlapping Community Quality Metrics
• Clubmark: a Parallel Isolation Framework for Benchmarking and Profiling Clustering Algorithms on NUMA Architectures
• Efficient Detection of Communities with Significant Overlaps in Networks: Partial Community Merger Algorithm