Social well-being analysis using interval-valued fuzzy predicates

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.