Meta-validation of bipartite network projections

Abstract Monopartite projections of bipartite networks are useful tools for modeling indirect interactions in complex systems. The standard approach to identify significant links is statistical validation using a suitable null network model, such as the popular configuration model (CM) that constrains node degrees and randomizes everything else. However different CM formulations exist, depending on how constraints imposed which sets nodes. Here we systematically investigate application these validating same network, showing they lead results even when significance threshold used. Instead much better agreement obtained density validated links. We thus propose meta-validation allows model-specific thresholds signal strongest, at time obtain independent way hypothesis formulated. illustrate this procedure data scientific production world countries.