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Linguistic summarization of fuzzy social and economic networks: an application on the international trade network

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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.

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Acknowledgements

Serkan GENÇ was supported by The Scientific and Technological Research Council of Turkey (TÜBITAK) –BIDEB National Doctoral Fellowship Program.

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Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Gazi University, 06570, Ankara, Turkey

    Serkan Genç & Diyar Akay

  2. Department of Energy Systems Engineering, Faculty of Technology, Gazi University, 06500, Ankara, Turkey

    Fatih Emre Boran

  3. Machine Intelligence Institute, Iona College, New Rochelle, NY, 10805, USA

    Ronald R. Yager

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  1. Serkan Genç
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  2. Diyar Akay
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  4. Ronald R. Yager
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Genç, S., Akay, D., Boran, F.E. et al. Linguistic summarization of fuzzy social and economic networks: an application on the international trade network. Soft Comput 24, 1511–1527 (2020). https://doi.org/10.1007/s00500-019-03982-9

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