Recently, social networks have become a major trend of computing and social paradigms. We realize that intuitionistic fuzzy concepts have a lot of potentials to be applied in the field of social networks. Therefore, in this thesis, we propose a novel similarity measure between intuitionistic fuzzy sets and intuitionistic fuzzy social graphs to model and analyze intuitionistic fuzzy social relational networks model which contain positive relationships and negative relationships between actors. We also show some properties of intuitionistic fuzzy relations between vertices in intuitionistic fuzzy social graphs. Then, we propose the concept of the strength of connectedness between vertices, having at most k edges between them, in an intuitionistic fuzzy social graph and define the intuitionistic fuzzy level-cut of the strength of connectedness between vertices. In order to measure the importance of a vertex in an intuitionistic fuzzy social graph, we propose the concept of the degree of centrality of a vertex in intuitionistic fuzzy social graphs. Then, we propose the concept of intuitionistic fuzzy clusters by the paradigm of computing with words. Finally, we propose queries processing techniques in an intuitionistic fuzzy social relational network. The proposed intuitionistic fuzzy social relational network model can overcome the drawback of Yager’s fuzzy social relational network model.

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