Similarity matrix average for aggregating multiplex networks

Abstract We introduce a methodology based on averaging similarity matrices with the aim of integrating layers multiplex network into single monoplex network. Multiplex networks are adopted for modelling wide variety real-world frameworks, such as multi-type relations in social, economic and biological structures. More specifically, used when different nature (layers) arise between set elements from given population (nodes). A possible approach analyzing consists aggregating (monoplex) which is valid representation—in some sense—of all layers. In order to obtain an aggregated network, we propose theoretical approach—along its practical implementation—which stems concept matrix average. This finally applied statistical journals, where three considered express journals co-citations, common authors editors, respectively.