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A Knowledge-Based Model for Polarity Shifters

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A Knowledge-Based Model for Polarity Shifters

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dc.contributor.author Blázquez-López, Yolanda es_ES
dc.date.accessioned 2023-01-09T08:34:25Z
dc.date.available 2023-01-09T08:34:25Z
dc.date.issued 2022-11-23
dc.identifier.uri http://hdl.handle.net/10251/191103
dc.description.abstract [EN] Polarity shifting can be considered one of the most challenging problems in the context of Sentiment Analysis. Polarity shifters, also known as contextual valence shifters (Polanyi and Zaenen 2004), are treated as linguistic contextual items that can increase, reduce or neutralise the prior polarity of a word called focus included in an opinion. The automatic detection of such items enhances the performance and accuracy of computational systems for opinion mining, but this challenge remains open, mainly for languages other than English. From a symbolic approach, we aim to advance in the automatic processing of the polarity shifters that affect the opinions expressed on tweets, both in English and Spanish. To this end, we describe a novel knowledge-based model to deal with three dimensions of contextual shifters: negation, quantification, and modality (or irrealis). es_ES
dc.description.sponsorship This work is part of the project grant PID2020-112827GB-I00, funded by MCIN/AEI/10.13039/501100011033, and the SMARTLAGOON project [101017861], funded by Horizon 2020 - European Union Framework Programme for Research and Innovation. es_ES
dc.language Inglés es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Journal of Computer-Assisted Linguistic Research es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Opinion mining es_ES
dc.subject Sentiment analysis es_ES
dc.subject Polarity shifting es_ES
dc.subject Negation es_ES
dc.subject Quantification es_ES
dc.subject Modality es_ES
dc.title A Knowledge-Based Model for Polarity Shifters es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/jclr.2022.18807
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-112827GB-I00/ES/SISTEMA INTELIGENTE MULTIMODAL BASADO EN CROWDSENSING PARA UN SERVICIO DE PREDICCION DE PROBLEMAS SOCIALES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/101017861 es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Blázquez-López, Y. (2022). A Knowledge-Based Model for Polarity Shifters. Journal of Computer-Assisted Linguistic Research. 6:87-107. https://doi.org/10.4995/jclr.2022.18807 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/jclr.2022.18807 es_ES
dc.description.upvformatpinicio 87 es_ES
dc.description.upvformatpfin 107 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 6 es_ES
dc.identifier.eissn 2530-9455
dc.relation.pasarela OJS\18807 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder European Commission es_ES
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