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dc.contributor.authorTorregrosa, Javier
dc.contributor.authorBello-Orgaz, Gema
dc.contributor.authorMartínez-Cámara, Eugenio
dc.contributor.authorSer, Javier Del
dc.contributor.authorCamacho, David
dc.date.accessioned2022-03-21T09:10:57Z
dc.date.available2022-03-21T09:10:57Z
dc.date.issued2022-12-12
dc.identifier.citationTorregrosa, Javier, Gema Bello-Orgaz, Eugenio Martínez-Cámara, Javier Del Ser, and David Camacho. “A Survey on Extremism Analysis Using Natural Language Processing: Definitions, Literature Review, Trends and Challenges.” Journal of Ambient Intelligence and Humanized Computing (January 12, 2022). doi:10.1007/s12652-021-03658-z.en
dc.identifier.issn1868-5137en
dc.identifier.urihttp://hdl.handle.net/11556/1297
dc.description.abstractExtremism has grown as a global problem for society in recent years, especially after the apparition of movements such as jihadism. This and other extremist groups have taken advantage of different approaches, such as the use of Social Media, to spread their ideology, promote their acts and recruit followers. The extremist discourse, therefore, is reflected on the language used by these groups. Natural language processing (NLP) provides a way of detecting this type of content, and several authors make use of it to describe and discriminate the discourse held by these groups, with the final objective of detecting and preventing its spread. Following this approach, this survey aims to review the contributions of NLP to the field of extremism research, providing the reader with a comprehensive picture of the state of the art of this research area. The content includes a first conceptualization of the term extremism, the elements that compose an extremist discourse and the differences with other terms. After that, a review description and comparison of the frequently used NLP techniques is presented, including how they were applied, the insights they provided, the most frequently used NLP software tools, descriptive and classification applications, and the availability of datasets and data sources for research. Finally, research questions are approached and answered with highlights from the review, while future trends, challenges and directions derived from these highlights are suggested towards stimulating further research in this exciting research area.en
dc.description.sponsorshipOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.en
dc.language.isoengen
dc.publisherSpringer Science and Business Media Deutschland GmbHen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleA survey on extremism analysis using natural language processing: definitions, literature review, trends and challengesen
dc.typearticleen
dc.identifier.doi10.1007/s12652-021-03658-zen
dc.rights.accessRightsopenAccessen
dc.subject.keywordsNatural language processingen
dc.subject.keywordsRadicalizationen
dc.subject.keywordsExtremismen
dc.subject.keywordsMachine learningen
dc.subject.keywordsDeep learningen
dc.identifier.essn1868-5145en
dc.journal.titleJournal of Ambient Intelligence and Humanized Computingen


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