Centrality with Entropy in Hypergraphs

Abstract

Entropy is used to measure uncertainty in complex systems. Hypergraphs provide structure for mathematically modeling real-world data. In this study, analyzes were made using entropy on the data in the hypergraph structure. The entropies of the nodes and hyperedges were calculated using the node degree and hyper edge degree. Their activities were found according to these values. The applicability of this method in weighted or unweighted relational structures was demonstrated through examples. In institutions with multiple departments and employees, the results obtained with the proposed method can be used to support decision-making processes.