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Social Well-Being Analysis Using Interval-Valued Fuzzy Predicates

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Computational Intelligence for Business Analytics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 953))

Abstract

Social well-being is one of the main goals of public policy. In this work, it is proposed a new methodology based on fuzzy predicates and interval-valued fuzzy logic for its computation and analysis, applied to urban areas of Argentina. The social well-being level of a territory is described through a fuzzy predicate, considering properties of different social indicators, and exploiting the advantages of the interval-valued fuzzy logic to deal with vague concepts. Fuzzy predicates allow to include knowledge about the meaning of social well-being and how it is traditionally measured, as well as linguistic descriptions involving social indicators. As a result, the social well-being level of each urban area is described by an interval. A method for interval comparing previously used in data clustering is applied here to rank the urban areas according to their social well-being levels. Results are consistent with those obtained using the known weighted average method. The approach proposed solves the problem of subjectivity in the evaluation of instances for comparative purposes, since once the fuzzy predicates are determined, the mathematical computation is the same for all the urban areas. This approach may have other interesting applications in the context of the Social Sciences, where new case studies are expected to be explored in the future.

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Acknowledgements

Authors acknowledge support from Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) from Argentina.

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Authors and Affiliations

  1. Institute of Scientific and Technological Research in Electronics (ICyTE), National University of Mar del Plata-CONICET, Mar del Plata, 2290, Buenos Aires, Argentina

    Diego S. Comas, Juan I. Pastore, Agustina Bouchet & Gustavo J. Meschino

  2. Studies of Work Group, School of Economic and Social Sciences, National University of Mar del Plata, Mar del Plata, 2290, Buenos Aires, Argentina

    Eugenio Actis Di Pasquale

Authors
  1. Diego S. Comas
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  2. Eugenio Actis Di Pasquale
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  3. Juan I. Pastore
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  4. Agustina Bouchet
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  5. Gustavo J. Meschino
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Corresponding author

Correspondence to Diego S. Comas .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, University of Alberta, Canada, AB, Canada

    Witold Pedrycz

  2. Department of Computer Science, School of Computing, Universidad de Jaén, Jaén, Spain

    Luis Martínez

  3. Accounting and Administration Faculty, Centre of Innovation Management Research for Entrepreneurial and Regional Development (CIGIDER), Autonomous University of Coahuila, Coah, Mexico

    Rafael Alejandro Espin-Andrade

  4. División Multidisciplinaria de Ciudad Universitaria, Universidad Autónoma de Ciudad Juárez, Chihuahua, Mexico

    Gilberto Rivera

  5. Department of Computing Science, Business Information Systems/ VLBA, Carl von Ossietzky Universität Oldenburg, Oldenburg, Niedersachsen, Germany

    Jorge Marx Gómez

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Comas, D.S., Actis Di Pasquale, E., Pastore, J.I., Bouchet, A., Meschino, G.J. (2021). Social Well-Being Analysis Using Interval-Valued Fuzzy Predicates. In: Pedrycz, W., Martínez, L., Espin-Andrade, R.A., Rivera, G., Marx Gómez, J. (eds) Computational Intelligence for Business Analytics. Studies in Computational Intelligence, vol 953. Springer, Cham. https://doi.org/10.1007/978-3-030-73819-8_22

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