Person: Gómez González, Daniel
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First Name
Daniel
Last Name
Gómez González
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Estudios estadísticos
Department
Estadística y Ciencia de los Datos
Area
Estadística e Investigación Operativa
Identifiers
3 results
Search Results
Now showing 1 - 3 of 3
Item Polarization measures in bi-partition networks based on fuzzy graphs(2022) Simón de Blas, Clara; Guevara Gil, Juan Antonio; Morillo, Jaime; Gómez González, DanielAbstract: In this paper we extend the definition of polarization in a network, by defining a new measure in fuzzy graphs. We will focus on the case of two communities in a fuzzy context. We present a well known problem in real life social networks to compare our results with the crisp case. Results shows improvements in detecting polarization masked in a crisp context.Item Measuring polarization: a fuzzy set theoretical approach(2020) Guevara Gil, Juan Antonio; Gómez González, Daniel; Robles Morales, José Manuel; Montero De Juan, Francisco Javier; Lesot, Marie-Jeanne; Vieira, Susana; Reformat, Marek Z.; Carvalho, João Paulo; Wilbik, Anna; Bouchon-Meunier, Bernadette; Yager, Ronald R.Abstract: The measurement of polarization has been studied over the last thirty years. Despite the different applied approaches, since polarization concept is complex, we find a lack of consensus about how it should be measured. This paper proposes a new approach to the measurement of the polarization phenomenon based on fuzzy set. Fuzzy approach provides a new perspective whose elements admit degrees of membership. Since reality is not black and white, a polarization measure should include this key characteristic. For this purpose we analyze polarization metric properties and develop a new risk of polarization measure using aggregation operators and overlapping functions. We simulate a sample of N = 391315 cases across a 5-likert-scale with different distributions to test our measure. Other polarization measures were applied to compare situations where fuzzy set approach offers different results, where membership functions have proved to play an essential role in the measurement. Finally, we want to highlight the new and potential contribution of fuzzy set approach to the polarization measurement which opens a new field to research on.Item A new approach to polarization modeling using Markov chains(2022) Guevara Gil, Juan Antonio; Gómez González, Daniel; Castro Cantalejo, Javier; Gutiérrez García-Pardo, Inmaculada; Robles Morales, José Manuel; Ciucci, Davide; Couso, Inés; Medina, Jesús; Ślęzak, Dominik; Petturiti, Davide; Bouchon-Meunier, Bernadette; Yager, Ronald R.Abstract: In this study, we approach the problem of polarization modeling with Markov Chains (PMMC). We propose a probabilistic model that provides an interesting approach to knowing what the probability for a specific attitudinal distribution is to get to an i.e. social, political, or affective Polarization. It also quantifies how many steps are needed to reach Polarization for that distribution. In this way, we can know how risky an attitudinal distribution is for reaching polarization in the near future. To do so, we establish some premises over which our model fits reality. Furthermore, we compare this probability with the polarization measure proposed by Esteban and Ray and the fuzzy polarization measure by Guevara et al. In this way, PMMC provides the opportunity to study in deep what is the performance of these polarization measures in specific conditions. We find that our model presents evidence that in fact, some distributions will presumably show higher risk than others even when the entire population holds the same attitude. In this sense, according to our model, we find that moderate/indecisive attitudes present a higher risk for polarization than extreme attitudes and should not be considered the same scenario despite the fact that the entire population maintains the same attitude.