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Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain

1
Faculty of Statistics, Complutense University Puerta de Hierro, 28040 Madrid, Spain
2
Instituto de Evaluación Sanitaria, Complutense University, 28040 Madrid, Spain
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Author to whom correspondence should be addressed.
Academic Editor: Josue Antonio Nescolarde Selva
Mathematics 2021, 9(4), 443; https://doi.org/10.3390/math9040443
Received: 2 January 2021 / Revised: 10 February 2021 / Accepted: 18 February 2021 / Published: 23 February 2021
(This article belongs to the Special Issue Artificial Intelligence with Applications of Soft Computing)
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. View Full-Text
Keywords: networks; community detection; extended fuzzy graphs; polarization; fuzzy sets; ordinal variation networks; community detection; extended fuzzy graphs; polarization; fuzzy sets; ordinal variation
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MDPI and ACS Style

Gutiérrez, I.; Guevara, J.A.; Gómez, D.; Castro, J.; Espínola, R. Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain. Mathematics 2021, 9, 443. https://doi.org/10.3390/math9040443

AMA Style

Gutiérrez I, Guevara JA, Gómez D, Castro J, Espínola R. Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain. Mathematics. 2021; 9(4):443. https://doi.org/10.3390/math9040443

Chicago/Turabian Style

Gutiérrez, Inmaculada; Guevara, Juan A.; Gómez, Daniel; Castro, Javier; Espínola, Rosa. 2021. "Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain" Mathematics 9, no. 4: 443. https://doi.org/10.3390/math9040443

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