Biclique communities.
We present a 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 biclique 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 biclique community detection algorithm provides a level of flexibility by incorporating independent clique thresholds for each of the nonoverlapping node sets in the bipartite network.
Lehmann
Sune
S
Center for Complex Network Research and Department of Physics, Northeastern University, Boston, Massachusetts 02115, USA.
Schwartz
Martin
M
Hansen
Lars Kai
LK