Overlapping communities detection based on spectral analysis of line graphs

Chun Gui, Ruisheng Zhang, Rongjing Hu, Guoming Huang and Jiaxuan Wei

Physica A: Statistical Mechanics and its Applications, 2018, vol. 498, issue C, 50-65

Abstract: Community in networks are often overlapping where one vertex belongs to several clusters. Meanwhile, many networks show hierarchical structure such that community is recursively grouped into hierarchical organization. In order to obtain overlapping communities from a global hierarchy of vertices, a new algorithm (named SAoLG) is proposed to build the hierarchical organization along with detecting the overlap of community structure. SAoLG applies the spectral analysis into line graphs to unify the overlap and hierarchical structure of the communities. In order to avoid the limitation of absolute distance such as Euclidean distance, SAoLG employs Angular distance to compute the similarity between vertices. Furthermore, we make a micro-improvement partition density to evaluate the quality of community structure and use it to obtain the more reasonable and sensible community numbers. The proposed SAoLG algorithm achieves a balance between overlap and hierarchy by applying spectral analysis to edge community detection. The experimental results on one standard network and six real-world networks show that the SAoLG algorithm achieves higher modularity and reasonable community number values than those generated by Ahn’s algorithm, the classical CPM and GN ones.

Keywords: Overlap; Hierarchical structure; Spectral analysis; Line graphs; Community detection (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:498:y:2018:i:c:p:50-65

DOI: 10.1016/j.physa.2018.01.025

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