Community detection and social network analysis based on the Italian wars of the 15th century

In this contribution we study social network modelling by using human interaction as a basis. To do so, we propose a new set of functions, affinities, designed to capture the nature of the local interactions among each pair of actors in a network. By using these functions, we develop a new community detection algorithm, the Borgia Clustering, where communities naturally arise from the multi-agent interaction in the network. We also discuss the effects of size and scale for communities regarding this case, as well as how we cope with the additional complexity present when big communities arise. Finally, we compare our community detection solution with other representative algorithms, finding favourable results.Javier Fumanal Idocin’s and Humberto Bustince’s research has been supported by the project TIN2016-77356-P (AEI/FEDER,UE).Oscar Cordón’s research was supported by the Spanish Ministry of Science, Innovation and Universities under grant EX-ASOCO (PGC2018-101216-B-I00), including, European Regional Development Funds (ERDF). Amparo Alonso-Betanzos’ research has been financially supported in part by the Spanish Ministerio de Economía y Competitividad (research project TIN2015-65069-C2-1-R), by European Union FEDER funds and by the Consellería de Industria of the Xunta de Galicia, Spain (research project GRC2014 /035). M. Minárová’s research has been funded by the project work was supported by the project APVV-17-0066