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Short Messages Spam Filtering Combining Personality Recognition and Sentiment Analysis.pdf (310.8Kb)
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Marc
Izenburua
Short Messages Spam Filtering Combining Personality Recognition and Sentiment Analysis
Egilea
Ezpeleta Gallastegi, EnaitzMondragon Unibertsitatea
Garitano, Iñaki ccMondragon Unibertsitatea
Zurutuza, UrkoMondragon Unibertsitatea
Egilea (beste erakunde batekoa)
Gómez Hidalgo, José María
Ikerketa taldea
Análisis de datos y ciberseguridad
Argitalpen data
2017
Argitaratzailea
World Scientific Publishing
Gako-hitzak
spam
polarity
SMS
sentiment analysis ... [+]
spam
polarity
SMS
sentiment analysis
security [-]
Laburpena
Currently, short communication channels are growing up due to the huge increase in the number of smartphones and online social networks users. This growth attracts malicious campaigns, such as spam ca ... [+]
Currently, short communication channels are growing up due to the huge increase in the number of smartphones and online social networks users. This growth attracts malicious campaigns, such as spam campaigns, that are a direct threat to the security and privacy of the users. While most researches are focused on automatic text classification, in this work we demonstrate the possibility of improving current short messages spam detection systems using a novel method. We combine personality recognition and sentiment analysis techniques to analyze Short Message Services (SMS) texts. 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 SMS spam classifiers and filters to each dataset in order to compare the results of each one. Taking into account the experimental results we analyze the real inuence of each feature and the combination of both. At the end, the best results are improved in terms of accuracy, reaching to a 99.01% and the number of false positive is reduced. [-]
URI
https://hdl.handle.net/20.500.11984/1181
Argitaratzailearen bertsioa
https://doi.org/10.1142/S0218488517400177
ISSN
0218-4885 Print
Non argitaratua
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems  Vol. 25. Nº. Suppl. 2. December, 2017
Dokumentu-mota
Artikulua
Bertsioa
Postprinta – Accepted Manuscript
Eskubideak
© World Scientific Publishing Company. Electronic version of an article published as International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. Vol. 25. Nº. Suppl. 2. December, 2017 https://www.worldscientific.com/worldscinet/ijufks
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