(untitled) (Revista Inclusiones, 2021)
In 2020 there were numerous studies on the impact of COVID-19 on the human body. In this paper we target to analyze the results from a sociologic survey over a very big group of responders whose answers comprise a big data set. We suggest an approach for analysis based on a simple acquisition of intuitionistic fuzzy sets where intuitionistic fuzzy degrees are assigned on the dimensions health, socio-economic status, social and family relations in the context of COVID-19 for the purposes of data analysis and visualization. The intuitionistic fuzzy sets of assessments are based on the classical Atanasov’s intuitionistic fuzzy set theory and the subsequent analyses use an approach for comparison between such sets based on Intuitionistic Fuzzy norms and distances. We apply the suggested approach on a real big dataset, obtained from the Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 8. COVID-19 Survey 1. Release version: 0.0.1. beta. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w8cabeta.001 (Börsch-Supan, A. 2020). As a result, EU countries are classified into several groups that segment the database in terms of health, socio-economic status, social and family relationships in the context of COVID-19. The methodology we offer is broad enough to be extended to other research or disciplines.