Randomizing Hypergraphs Preserving Two-mode Clustering Coefficient

Hypergraphs are data structures that capture the interactions between two or more nodes. By comparing random hypergraphs that preserve particular properties with an original hypergraph, we can analyze the impacts of those properties. In this study, we propose a method for generating random hypergraphs that preserve the pairwise joint degree distribution and the two-mode clustering coefficient. By the proposed method, we generated hypergraphs that preserve the average degree of the node and the degree of each node and approximately preserve the pairwise joint degree distribution and the two-mode clustering coefficient.