Overlapping Community Detection of Bipartite Networks Based on a Novel Community Density

Yubo Peng, Bofeng Zhang and Furong Chang
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Yubo Peng: School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China
Bofeng Zhang: School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China
Furong Chang: School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China

Future Internet, 2021, vol. 13, issue 4, 1-21

Abstract: Community detection plays an essential role in understanding network topology and mining underlying information. A bipartite network is a complex network with more important authenticity and applicability than a one-mode network in the real world. There are many communities in the network that present natural overlapping structures in the real world. However, most of the research focuses on detecting non-overlapping community structures in the bipartite network, and the resolution of the existing evaluation function for the community structure’s merits are limited. So, we propose a novel function for community detection and evaluation of the bipartite network, called community density D . And based on community density, a bipartite network community detection algorithm DSNE (Density Sub-community Node-pair Extraction) is proposed, which is effective for overlapping community detection from a micro point of view. The experiments based on artificially-generated networks and real-world networks show that the DSNE algorithm is superior to some existing excellent algorithms; in comparison, the community density (D) is better than the bipartite network’s modularity.

Keywords: overlapping community; bipartite network; community detection; community density (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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