{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T16:19:48Z","timestamp":1769530788479,"version":"3.49.0"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2020,1,14]],"date-time":"2020-01-14T00:00:00Z","timestamp":1578960000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,1,24]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Unsolicited 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\u2019 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.<\/jats:p>","DOI":"10.1093\/jigpal\/jzz073","type":"journal-article","created":{"date-parts":[[2019,11,12]],"date-time":"2019-11-12T20:10:02Z","timestamp":1573589402000},"page":"83-94","source":"Crossref","is-referenced-by-count":14,"title":["Novel email spam detection method using sentiment analysis and personality recognition"],"prefix":"10.1093","volume":"28","author":[{"given":"Enaitz","family":"Ezpeleta","sequence":"first","affiliation":[{"name":"Electronics and Computing Department, Mondragon University, Goiru Kalea, 2, 20500 Arrasate-Mondrag\u00f3n, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"I\u00f1aki","family":"Velez de Mendizabal","sequence":"additional","affiliation":[{"name":"Electronics and Computing Department, Mondragon University, Goiru Kalea, 2, 20500 Arrasate-Mondrag\u00f3n, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 Mar\u00eda G\u00f3mez","family":"Hidalgo","sequence":"additional","affiliation":[{"name":"Pragsis Technologies Manuel Tovar, 43-53, Fuencarral, 28034 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Urko","family":"Zurutuza","sequence":"additional","affiliation":[{"name":"Electronics and Computing Department, Mondragon University, Goiru Kalea, 2, 20500 Arrasate-Mondrag\u00f3n, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,1,14]]},"reference":[{"key":"2020012910165218100_ref1","doi-asserted-by":"crossref","first-page":"153","DOI":"10.4236\/cn.2011.33019","article-title":"Survey on spam filtering techniques","volume":"3","author":"Saadat","year":"2011","journal-title":"Communications and 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