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Relevance as an enhancer of votes on Twitter

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Relevance as an enhancer of votes on Twitter

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dc.contributor.author Arroba Rimassa, Jorge es_ES
dc.contributor.author Llopis, Fernando es_ES
dc.contributor.author Munoz Guillena, Rafael es_ES
dc.date.accessioned 2018-11-02T11:16:30Z
dc.date.available 2018-11-02T11:16:30Z
dc.date.issued 2018-09-07
dc.identifier.isbn 9788490486894
dc.identifier.uri http://hdl.handle.net/10251/111754
dc.description.abstract [EN] The concept of the influence of Katz and Lazarfeld given in the last century has evolved thanks to the appearance of Social Networks and especially Twitter. Because this microblogging has allowed candidates for any election process to be closer to their electors and also allows an analysis of the contents of the messages to determine their polarity. The relevance of the messages that measure the level of influence that can be had in the voters, incorporated into the traditional analysis of the Social Networks allow to have a greater degree of precision in the electoral predictions that are made using natural language processing, NLP. We have introduced in the methodology that we propose a mechanism to enhance the votes of those messages that have a greater relevance and turn them into votes in order to improve the predictability of the electoral results. The proposed methodology was applied in the election for President of the Republic of Ecuador that was held on February 19, 2017, obtaining a Mean Average Error, MAE = 1.4 that demonstrates the relevance of incorporating the variable Relevance as an enhancer of votes. es_ES
dc.description.sponsorship This research work has been partially funded by the University of Alicante, Generalitat Valenciana , Spanish Government, Ministerio de Educación, Cultura y Deporte and ASAP - Ayudas Fundación BBVA a equipos de investigación científica 2016(FUNDACIONBBVA2-16PREMIO) through the projects, TIN2015- 65100-R, TIN2015-65136-C2-2-R, PROMETEOII/2014/001, GRE16- 01: “Plataforma inteligente para recuperación, análisis y representación de la información generada por usuarios en Internet” and “Análisis de Sentimientos Aplicado a la Prevención del Suicidio en las Redes Sociales” (PR16_SOC_0013). es_ES
dc.format.extent 8 es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation.ispartof 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018) es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Web data es_ES
dc.subject Internet data es_ES
dc.subject Big data es_ES
dc.subject QCA es_ES
dc.subject PLS es_ES
dc.subject SEM es_ES
dc.subject Conference es_ES
dc.subject Relevance es_ES
dc.subject Twitter es_ES
dc.subject Election process es_ES
dc.title Relevance as an enhancer of votes on Twitter es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.4995/CARMA2018.2018.8311
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2015-65136-C2-2-R/ES/EXTRACCION DE CONOCIMIENTO PARA ENRIQUECIMIENTO SEMANTICO DE LAS ENTIDADES DIGITALES/
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2015-65100-R/ES/REPRESENTACION CANONICA Y TRANSFORMACIONES DE LOS TEXTOS APLICADO A LAS TECNOLOGIAS DEL LENGUAJE HUMANO/
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEOII%2F2014%2F001/
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Arroba Rimassa, J.; Llopis, F.; Munoz Guillena, R. (2018). Relevance as an enhancer of votes on Twitter. En 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018). Editorial Universitat Politècnica de València. 63-70. https://doi.org/10.4995/CARMA2018.2018.8311 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename CARMA 2018 - 2nd International Conference on Advanced Research Methods and Analytics es_ES
dc.relation.conferencedate Julio 12-13,2018 es_ES
dc.relation.conferenceplace Valencia, Spain es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/CARMA/CARMA2018/paper/view/8311 es_ES
dc.description.upvformatpinicio 63 es_ES
dc.description.upvformatpfin 70 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\8311 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Universidad de Alicante
dc.contributor.funder Fundación BBVA


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