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Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter

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Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter

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dc.contributor.author Frenda, Simona es_ES
dc.contributor.author Ghanem, Bilal es_ES
dc.contributor.author Montes-y-Gómez, Manuel es_ES
dc.contributor.author Rosso, Paolo es_ES
dc.date.accessioned 2021-01-12T21:02:59Z
dc.date.available 2021-01-12T21:02:59Z
dc.date.issued 2019 es_ES
dc.identifier.issn 1064-1246 es_ES
dc.identifier.uri http://hdl.handle.net/10251/158846
dc.description.abstract [EN] Patriarchal behavior, such as other social habits, has been transferred online, appearing as misogynistic and sexist comments, posts or tweets. This online hate speech against women has serious consequences in real life, and recently, various legal cases have arisen against social platforms that scarcely block the spread of hate messages towards individuals. In this difficult context, this paper presents an approach that is able to detect the two sides of patriarchal behavior, misogyny and sexism, analyzing three collections of English tweets, and obtaining promising results. es_ES
dc.description.sponsorship The work of Simona Frenda and Paolo Rosso was partially funded by the Spanish MINECO under the research project SomEMBED (TIN2015-71147-C2-1-P). We also thank the support of CONACYT-Mexico (project FC-2410). es_ES
dc.language Inglés es_ES
dc.publisher IOS Press es_ES
dc.relation.ispartof Journal of Intelligent & Fuzzy Systems es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Misogyny detection es_ES
dc.subject Sexism detection es_ES
dc.subject Linguistic analysis es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3233/JIFS-179023 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CONACyT//FC 2016-2410/ 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/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096212-B-C31/ES/DESINFORMACION Y AGRESIVIDAD EN SOCIAL MEDIA: AGREGANDO INFORMACION Y ANALIZANDO EL LENGUAJE/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Frenda, S.; Ghanem, B.; Montes-Y-Gómez, M.; Rosso, P. (2019). Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter. Journal of Intelligent & Fuzzy Systems. 36(5):4743-4752. https://doi.org/10.3233/JIFS-179023 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3233/JIFS-179023 es_ES
dc.description.upvformatpinicio 4743 es_ES
dc.description.upvformatpfin 4752 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 36 es_ES
dc.description.issue 5 es_ES
dc.relation.pasarela S\388658 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Ministerio de Economía y Empresa es_ES
dc.contributor.funder Consejo Nacional de Ciencia y Tecnología, México es_ES
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