A Model to Represent Human Social Relationships in Social Network Graphs

Human social relationships are a key component of emerging complex techno-social systems such as socially-centric platforms based on the interactions between humans and ICT technologies. Therefore, the models of human social relationships are fundamental to characterise these systems and study the performance of socially-centric platforms depending on the social context where they operate. The goal of this paper is presenting a generative model for building synthetic human social network graphs where the properties of social relationships are accurately reproduced. The model goes well beyond a binary approach, whereby edges between nodes, if existing, are all of the same type. It sets the properties of each social link, by incorporating fundamental results from the anthropology literature. The synthetic networks it generates accurately reproduce both the macroscopic structure (e.g., its diameter and clustering coefficient), and the microscopic structure (e.g., the properties of the tie strength of individual social links) of human social networks. We compare generated networks with a large-scale social network data set, validating that the model is able to produce graphs with the same structural properties of human-social-network graphs. Moreover, we characterise the impact of the model parameters on the synthetic graph properties.