Entropy-Based Null Models for the Analysis of Bipartite Networks
In a bipartite rating network, edges represent reviews of products purchased by consumers and are weighted by the numerical score received (i.e. Amazon review system). We provide theoretical tools for their analysis extending the procedure in [1, 2, 3]. Given an observed rating network, its random counterpart is given by a gran canonical ensemble of graphs, which probability distribution is defined maximising the entropy over a set of constraints per node, i.e. the observed degree for each possible score (Bipartite Score Configuration Model, BiSCM).