RT Journal Article
T1 Community detection problem based on polarization measures: an application to Twitter: the COVID-19 case in Spain
A1 Gutiérrez García-Pardo, Inmaculada
A1 Gómez González, Daniel
A1 Castro Cantalejo, Javier
A1 Guevara Gil, Juan Antonio
A1 Espínola Vílchez, María Rosario
A2 Nescolarde Selva, Josue Antonio
AB 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.
PB MDPI
YR 2021
FD 2021-02-23
LK https://hdl.handle.net/20.500.14352/100076
UL https://hdl.handle.net/20.500.14352/100076
LA eng
NO 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, doi:10.3390/math9040443.
DS Docta Complutense
RD 17 may 2025