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Methodology for Measuring Individual Affective Polarization Using Sentiment Analysis in Social Networks

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Methodology for Measuring Individual Affective Polarization Using Sentiment Analysis in Social Networks

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dc.contributor.author Martínez-España, Raquel es_ES
dc.contributor.author Fernández-Pedauye, Julio es_ES
dc.contributor.author Giner-Pérez de Lucía, José es_ES
dc.contributor.author Rojo-Martínez, Jose Miguel es_ES
dc.contributor.author Bakdid-Albane, Kaoutar es_ES
dc.contributor.author García-Escribano, Juan José es_ES
dc.date.accessioned 2024-11-21T19:11:28Z
dc.date.available 2024-11-21T19:11:28Z
dc.date.issued 2024 es_ES
dc.identifier.uri http://hdl.handle.net/10251/212144
dc.description.abstract [EN] Affective polarization has important consequences for societies and institutions. At the institutional level, it hinders agreement among political actors, which damages the stability of the system. At the social level, it increases tensions and conflicts between people, damaging coexistence. Until now, affective polarization has been studied essentially through surveys, which are generally very costly if large and representative samples are to be obtained and in which the answers of the interviewees may not be totally sincere. Through this article, we apply sentiment analysis techniques to measure affective polarization without resorting to surveys, simply by monitoring the non-self-reported behavior of individuals in social networks. To do that, a novel methodology and a new indicator of affective polarization has been proposed using data from social networks. The proposed methodology and new indicator have been applied to the real case study of the regional elections in Spain, specifically to the autonomous Region of Murcia. The application of the methodology has been satisfactory, as well as that of the new indicator of affective polarization, providing a cost-effective way of calculating polarization. The results show that all political groups are polarized to a greater or lesser extent. Furthermore, the results conclude that the winning ideology in the elections, i.e., the right, was the one whose supporters behaved differently from the supporters of other ideologies. es_ES
dc.description.sponsorship This work was supported by the Science and Technology Agency of the Region of Murcia under Grant 21876/PI/2022. The work of Jose Miguel Rojo-Martinez and Kaoutar Bakdid-Albane was supported by the Ministry of Universities of the Spanish Government through the FPU under Grant FPU20/01033 and Grant FPU21/04363. The work of Jose Giner-Perez de Lucia was supported in part by the CIN/AEI/10.13039/501100011033 under Grant TED2021-130890B, and in part by the European Union NextGeneration EU/PRTR. es_ES
dc.language Inglés es_ES
dc.publisher Institute of Electrical and Electronics Engineers es_ES
dc.relation.ispartof IEEE Access es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Social networking (online) es_ES
dc.subject Sentiment analysis es_ES
dc.subject Surveys es_ES
dc.subject Sociology es_ES
dc.subject Voting es_ES
dc.subject Technological innovation es_ES
dc.subject Sensors es_ES
dc.subject Polarization es_ES
dc.subject Natural language processing es_ES
dc.subject Affective polarization es_ES
dc.subject Lexicon-based techniques es_ES
dc.subject Sentiment analysis,social networks es_ES
dc.title Methodology for Measuring Individual Affective Polarization Using Sentiment Analysis in Social Networks es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1109/ACCESS.2024.3431999 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/f SéNeCa//21876%2FPI%2F22//Polarización afectiva en la Región de Murcia. Un estudio sobre sus causas/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MIU//FPU20%2F01033/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MIU//FPU21%2F04363/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//TED2021-130890B-C21/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.description.bibliographicCitation Martínez-España, R.; Fernández-Pedauye, J.; Giner-Pérez De Lucía, J.; Rojo-Martínez, JM.; Bakdid-Albane, K.; García-Escribano, JJ. (2024). Methodology for Measuring Individual Affective Polarization Using Sentiment Analysis in Social Networks. IEEE Access. 12:102035-102049. https://doi.org/10.1109/ACCESS.2024.3431999 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1109/ACCESS.2024.3431999 es_ES
dc.description.upvformatpinicio 102035 es_ES
dc.description.upvformatpfin 102049 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.identifier.eissn 2169-3536 es_ES
dc.relation.pasarela S\525087 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Ministerio de Universidades es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia es_ES


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