Person:
Gómez González, Daniel

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First Name
Daniel
Last Name
Gómez González
URI
https://hdl.handle.net/20.500.14352/77430
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Estudios estadísticos
Department
Estadística y Ciencia de los Datos
Area
Estadística e Investigación Operativa
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20211
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Author: Guevara Gil, Juan Antonio × Subject: 004.6 ×

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    Community detection problem based on polarization measures: an application to Twitter: the COVID-19 case in Spain
    (Mathematics, 2021) Gutiérrez García-Pardo, Inmaculada; Gómez González, Daniel; Castro Cantalejo, Javier; Guevara Gil, Juan Antonio; Espínola Vílchez, María Rosario; Nescolarde Selva, Josue Antonio
    In this paper, we address one of the most important topics in the field of Social Networks Analysis: the community detection problem with additional information. That additional information is modeled by a fuzzy measure that represents the risk of polarization. Particularly, we are interested in dealing with the problem of taking into account the polarization of nodes in the community detection problem. Adding this type of information to the community detection problem makes it more realistic, as a community is more likely to be defined if the corresponding elements are willing to maintain a peaceful dialogue. The polarization capacity is modeled by a fuzzy measure based on the JDJpol measure of polarization related to two poles. We also present an efficient algorithm for finding groups whose elements are no polarized. Hereafter, we work in a real case. It is a network obtained from Twitter, concerning the political position against the Spanish government taken by several influential users. We analyze how the partitions obtained change when some additional information related to how polarized that society is, is added to the problem.