Is it Correct to Project and Detect? Assessing Performance of Community Detection on Unipartite Projections of Bipartite Networks

Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 812)


Many real-world systems can be represented by bipartite networks that link two classes of node. However, methods for analysing bipartite networks are not as well-developed as those for unipartite networks. In particular, community detection in bipartite networks is often approached by projecting the network onto a unipartite network incorporating just one of the bipartite node classes. Here we apply a simple model to generate bipartite networks with prescribed community structure and then test the performance of community detection using four different unipartite projection schemes. Several important performance issues emerge from this treatment, particularly when the original bipartite networks have a long-tailed degree distribution. We find that a “hyperbolic” projection scheme mitigates performance issues to some extent, but conclude that care must be taken when interpreting community detection algorithm performance on projected networks. These findings have implications for any scenario where a unipartite projection is analysed in place of a bipartite system, including common applications to online social networks, social media and scientific collaboration networks.


Community Detection Unipartite Networks Long-tailed Degree Distribution Node Bipartition Hyperbolic Weight 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



TC is funded by an EPSRC Research Studentship (grant number EP/M506527/1). HW and IW acknowledge funding from ESRC (grant number ES/N012283/1) and NERC (grant number NE/P017436/1). We thank the two anonymous reviewers for their comments and the resulting improvements to this manuscript.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.College of Engineering, Mathematics and Physical Sciences, Harrison Building, Streatham CampusUniversity of ExeterExeterUK

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