Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Community Detection Problem Based on Polarization Measures. An application to Twitter: the COVID-19 case in Spain

Version 1 : Received: 2 January 2021 / Approved: 5 January 2021 / Online: 5 January 2021 (11:18:08 CET)

How to cite: Gutiérrez García-Pardo, I.; Guevara Gil, J.A.; Gómez González, D.; Castro Cantalejo, J.; Espínola Vílchez, R. Community Detection Problem Based on Polarization Measures. An application to Twitter: the COVID-19 case in Spain. Preprints 2021, 2021010080 (doi: 10.20944/preprints202101.0080.v1). Gutiérrez García-Pardo, I.; Guevara Gil, J.A.; Gómez González, D.; Castro Cantalejo, J.; Espínola Vílchez, R. Community Detection Problem Based on Polarization Measures. An application to Twitter: the COVID-19 case in Spain. Preprints 2021, 2021010080 (doi: 10.20944/preprints202101.0080.v1).

Abstract

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 possibility 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 probably 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.

Subject Areas

Networks; Community Detection; Extended Fuzzy Graphs; Polarization; Fuzzy Sets; Ordinal Variation

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