Sociocentric SNA on fuzzy graph social network model

Abstract

The paper presents a scalable and generalized approach to social network analysis using fuzzy graph theory. It proposes an intelligent sociocentric approach that calculates the degree of potential relationship of a social network of finite size by proposing a fuzzy graph social network model. It takes into account social entity functional and relational attributes simultaneously. It computes the degree of potential relationship of a social network in two steps. The first step computes the fuzzy pairwise relationship between all social nodes or entities by incorporating the proposed fuzzy node activeness index parameter with an online and offline communication relationship. The second step further uses all fuzzy pairwise relationships calculated in the first step to calculate the degree of potential relationship of a social network. It uses an astute function that utilizes weighted arithmetic and geometric means of the relationships between entities. It also uses two weights—betweenness and closeness centrality of an entity in the social network. The paper performs the experimental work on a small WhatsApp social network of undergraduate students in the university for 6 months. Hence, the paper proposes the degree of potential relationship in social networks, which may be used as a global parameter to compare different social networks by simultaneously incorporating social node's functional and relational attributes.