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Irony Detection in Twitter: The Role of Affective Content

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Irony Detection in Twitter: The Role of Affective Content

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dc.contributor.author Hernandez-Farias, Delia Irazu es_ES
dc.contributor.author Patti, Viviana es_ES
dc.contributor.author Rosso, Paolo es_ES
dc.date.accessioned 2017-05-30T08:51:04Z
dc.date.available 2017-05-30T08:51:04Z
dc.date.issued 2016-08
dc.identifier.issn 1533-5399
dc.identifier.uri http://hdl.handle.net/10251/81998
dc.description © ACM 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Internet Technology, Vol. 16. http://dx.doi.org/10.1145/2930663. es_ES
dc.description.abstract [EN] Irony has been proven to be pervasive in social media, posing a challenge to sentiment analysis systems. It is a creative linguistic phenomenon where affect-related aspects play a key role. In this work, we address the problem of detecting irony in tweets, casting it as a classification problem. We propose a novel model that explores the use of affective features based on a wide range of lexical resources available for English, reflecting different facets of affect. Classification experiments over different corpora show that affective information helps in distinguishing among ironic and nonironic tweets. Our model outperforms the state of the art in almost all cases. es_ES
dc.description.sponsorship The National Council for Science and Technology (CONACyT Mexico) has funded the research work of Delia Irazu Hernandez Farias (Grant No. 218109/313683 CVU-369616). The work of Viviana Patti was partially carried out at the Universitat Politecnica de Valencia within the framework of a fellowship of the University of Turin cofunded by Fondazione CRT (World Wide Style Program 2). The work of Paolo Rosso has been partially funded by the SomEMBED TIN2015-71147-C2-1-P MINECO research project and by the Generalitat Valenciana under the grant ALMAMATER (PrometeoII/2014/030).
dc.language Inglés es_ES
dc.publisher Association for Computing Machinery (ACM) es_ES
dc.relation.ispartof ACM Transactions on Internet Technology es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Irony detection es_ES
dc.subject Figurative language processing es_ES
dc.subject Affective resources es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Irony Detection in Twitter: The Role of Affective Content es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1145/2930663
dc.relation.projectID info:eu-repo/grantAgreement/CONACyT//218109%2F313683 CVU-369616/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2015-71147-C2-1-P/ES/COMPRENSION DEL LENGUAJE EN LOS MEDIOS DE COMUNICACION SOCIAL - REPRESENTANDO CONTEXTOS DE FORMA CONTINUA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEOII%2F2014%2F030/ES/ Adaptive learning and multimodality in machine translation and text transcription/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Hernandez-Farias, DI.; Patti, V.; Rosso, P. (2016). Irony Detection in Twitter: The Role of Affective Content. ACM Transactions on Internet Technology. 16(3):19:1-19:24. https://doi.org/10.1145/2930663 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1145/2930663 es_ES
dc.description.upvformatpinicio 19:1 es_ES
dc.description.upvformatpfin 19:24 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 16 es_ES
dc.description.issue 3 es_ES
dc.relation.senia 326666 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad
dc.contributor.funder Generalitat Valenciana
dc.contributor.funder Consejo Nacional de Ciencia y Tecnología, México
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