Bi-clique Communities

TL;DR

This paper introduces a new method for detecting overlapping communities in bipartite networks using an extension of the $k$-clique algorithm, preserving structural information and allowing flexible thresholds.

Contribution

It presents a novel bi-clique community detection algorithm tailored for bipartite networks, improving upon existing methods by retaining structural details and offering adjustable parameters.

Findings

Effective detection of overlapping bicliques in bipartite networks

Preserves structural information compared to one-mode projection

Provides flexible thresholds for different node sets

Abstract

We present a novel method for detecting communities in bipartite networks. Based on an extension of the $k$-clique community detection algorithm, we demonstrate how modular structure in bipartite networks presents itself as overlapping bicliques. If bipartite information is available, the bi-clique community detection algorithm retains all of the advantages of the $k$-clique algorithm, but avoids discarding important structural information when performing a one-mode projection of the network. Further, the bi-clique community detection algorithm provides a new level of flexibility by incorporating independent clique thresholds for each of the non-overlapping node sets in the bipartite network.