Search results for "bipartite networks"
showing 2 items of 2 documents
Insurance fraud detection: A statistically validated network approach
2022
Fraud is a social phenomenon, and fraudsters often collaborate with other fraudsters, taking on different roles. The challenge for insurance companies is to implement claim assessment and improve fraud detection accuracy. We developed an investigative system based on bipartite networks, highlighting the relationships between subjects and accidents or vehicles and accidents. We formalize filtering rules through probability models and test specific methods to assess the existence of communities in extensive networks and propose new alert metrics for suspicious structures. We apply the methodology to a real database-the Italian Antifraud Integrated Archive-and compare the results to out-of-sam…
Sensitivity of bipartite network analyses to incomplete sampling and taxonomic uncertainty
2023
Bipartite network analysis is a powerful tool to study the processes structuring interactions in ecological communities. In applying the method, it is assumed that the sampled interactions provide an accurate representation of the actual community. However, acquiring a representative sample may be difficult as not all species are equally abundant or easily identifiable. Two potential sampling issues can compromise the conclusions of bipartite network analyses: failure to capture the full range of interactions (sampling completeness) and use of a taxonomic level higher than species to evaluate the network (taxonomic resolution). We asked how commonly used descriptors of bipartite antagonisti…