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Bipartite user-object networks are becoming increasingly popular inrepresenting user interaction data in a web or e-commerce environment. Theyhave certain characteristics and challenges that differentiates them from otherbipartite networks. This paper analyzes the properties of five real worlduser-object networks. In all cases we found a heavy tail object degreedistribution with popular objects connecting together a large part of the userscausing significant edge inflation in the projected users network. We propose anovel edge weighting strategy based on tf-idf and show that the new schemeimproves both the density and the quality of the community structure in theprojections. The improvement is also noticed when comparing to partially randomnetworks.

Using tf-idf as an edge weighting scheme in user-object bipartite networks