Abstract
Although plenty of techniques such as link prediction, clustering, and position analysis have been proposed to analyze social and economic networks and patterns of social and economic relationships in various fields, few studies have addressed the transformation of social and economic network data into the knowledge in the form of linguistic summaries. In this study, we propose, for the first time in the literature, iteration, reciprocal and branching-based linguistic summary forms taking into account both the attributes (features) of social and economic actors and the relations between them. We then develop methods for evaluating the degree of truth of the suggested linguistic summary forms by leveraging generalized quantifiers, specifically semi-fuzzy and polyadic quantifiers. The advantages and applicability of the proposed linguistic summary forms are illustrated on the international trade network.