2026-04-21T12:25:33Zhttps://ebiltegia.mondragon.edu/oai/request

oai:ebiltegia.mondragon.edu:20.500.11984/63672024-05-24T11:21:23Zcom_20.500.11984_473col_20.500.11984_478

00925njm 22002777a 4500 dc Velez de Mendizabal, Iñaki author Zurutuza, Urko author Ezpeleta, Enaitz author 2020 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’ 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. 1368-9894 https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=154845 https://hdl.handle.net/20.500.11984/6367 spam polarity personality sentiment analysis Novel email spam detection method using sentiment analysis and personality recognition