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dc.contributor.authorVelez de Mendizabal, Iñaki
dc.contributor.authorZurutuza, Urko
dc.contributor.authorEzpeleta, Enaitz
dc.contributor.otherGómez Hidalgo, José María
dc.date.accessioned2024-04-24T08:59:39Z
dc.date.available2024-04-24T08:59:39Z
dc.date.issued2020
dc.identifier.issn1368-9894en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=154845en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/6367
dc.description.abstractUnsolicited email campaigns remain as one of the biggest threats affecting millions of users per day. During the past years several techniques to detect unsolicited emails have been developed. This work provides means to validate the hypothesis that the identification of the email messages’ intention can be approached by sentiment analysis and personality recognition techniques. These techniques will provide new features that improve current spam classification techniques. We combine personality recognition and sentiment analysis techniques to analyse email content. We enrich a publicly available dataset adding these features, first separately and after in combination, of each message to the dataset, creating new datasets. We apply several combinations of the best email spam classifiers and filters to each dataset in order to compare results.en
dc.language.isoengen
dc.publisherOxford Academicen
dc.rights© 2020 The Author(s)en
dc.subjectspamen
dc.subjectpolarityen
dc.subjectpersonalityen
dc.subjectsentiment analysisen
dc.titleNovel email spam detection method using sentiment analysis and personality recognitionen
dcterms.accessRightshttp://purl.org/coar/access_right/c_abf2en
dcterms.sourceLogic Journal of the IGPLen
local.contributor.groupAnálisis de datos y ciberseguridades
local.description.peerreviewedtrueen
local.identifier.doihttps://doi.org/10.1093/jigpal/jzz073en
local.contributor.otherinstitutionPragsis Technologies
local.source.detailsVol. 28. N. 1. Pp. 83–94. February, 2020
oaire.format.mimetypeapplication/pdfen
oaire.file$DSPACE\assetstoreen
oaire.resourceTypehttp://purl.org/coar/resource_type/c_6501en
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaen


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