Community detection problem based on polarization measures:an application to Twitter: the COVID-19 case in Spain
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866913226130718720 |
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| author | Gutiérrez, Inmaculada Guevara, Juan Antonio Gómez, Daniel Castro, Javier Espínola, Rosa |
| author_facet | Gutiérrez, Inmaculada Guevara, Juan Antonio Gómez, Daniel Castro, Javier Espínola, Rosa |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2402_05028 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Community detection problem based on polarization measures:an application to Twitter: the COVID-19 case in Spain Gutiérrez, Inmaculada Guevara, Juan Antonio Gómez, Daniel Castro, Javier Espínola, Rosa Social and Information Networks Statistics Theory Physics and Society 62.08, G.3 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. |
| title | Community detection problem based on polarization measures:an application to Twitter: the COVID-19 case in Spain |
| topic | Social and Information Networks Statistics Theory Physics and Society 62.08, G.3 |
| url | https://arxiv.org/abs/2402.05028 |