AN INTUITIONISTIC FUZZY APPROACH FOR COVID-19 SURVEY ANALYTICS

Resumen

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.