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

Author

Listed:
  • Inmaculada Gutiérrez

    (Faculty of Statistics, Complutense University Puerta de Hierro, 28040 Madrid, Spain)

  • Juan Antonio Guevara

    (Faculty of Statistics, Complutense University Puerta de Hierro, 28040 Madrid, Spain)

  • Daniel Gómez

    (Faculty of Statistics, Complutense University Puerta de Hierro, 28040 Madrid, Spain
    Instituto de Evaluación Sanitaria, Complutense University, 28040 Madrid, Spain)

  • Javier Castro

    (Faculty of Statistics, Complutense University Puerta de Hierro, 28040 Madrid, Spain
    Instituto de Evaluación Sanitaria, Complutense University, 28040 Madrid, Spain)

  • Rosa Espínola

    (Faculty of Statistics, Complutense University Puerta de Hierro, 28040 Madrid, Spain
    Instituto de Evaluación Sanitaria, Complutense University, 28040 Madrid, Spain)

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 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 J D J p o l 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.

Suggested Citation

  • Inmaculada Gutiérrez & Juan Antonio Guevara & Daniel Gómez & Javier Castro & Rosa Espínola, 2021. "Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain," Mathematics, MDPI, vol. 9(4), pages 1-27, February.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:4:p:443-:d:504262
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    References listed on IDEAS

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    Cited by:

    1. Massimo Aria & Corrado Cuccurullo & Luca D’Aniello & Michelangelo Misuraca & Maria Spano, 2022. "Thematic Analysis as a New Culturomic Tool: The Social Media Coverage on COVID-19 Pandemic in Italy," Sustainability, MDPI, vol. 14(6), pages 1-22, March.
    2. Inmaculada Gutiérrez & Daniel Gómez & Javier Castro & Rosa Espínola, 2022. "From Fuzzy Information to Community Detection: An Approach to Social Networks Analysis with Soft Information," Mathematics, MDPI, vol. 10(22), pages 1-22, November.

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