Abstract : Stylometry is a form of authorship attribution that relies on the linguistic information found in a document. While there has been significant work in stylometry, most research focuses on the closed-world problem where the author of the document is in a known suspect set. For open-world problems where the author may not be in the suspect set, traditional classification methods are ineffective. This paper proposes the “classify-verify” method that augments classification with a binary verification step evaluated on stylometric datasets. This method, which can be generalized to any domain, significantly outperforms traditional classifiers in open-world settings and yields an F1-score of 0.87, comparable to traditional classifiers in closed-world settings. Moreover, the method successfully detects adversarial documents where authors deliberately change their styles, a problem for which closed-world classifiers fail.
Gilbert Peterson; Sujeet Shenoi. 10th IFIP International Conference on Digital Forensics (DF), Jan 2014, Vienna, Austria. Springer, IFIP Advances in Information and Communication Technology, AICT-433, pp.185-205, 2014, Advances in Digital Forensics X. 〈10.1007/978-3-662-44952-3_13〉
https://hal.inria.fr/hal-01393771
Contributeur : Hal Ifip
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Soumis le : mardi 8 novembre 2016 - 10:48:53
Dernière modification le : vendredi 1 décembre 2017 - 01:17:02
Document(s) archivé(s) le : mardi 14 mars 2017 - 22:15:50
Ariel Stolerman, Rebekah Overdorf, Sadia Afroz, Rachel Greenstadt. Breaking the Closed-World Assumption in Stylometric Authorship Attribution. Gilbert Peterson; Sujeet Shenoi. 10th IFIP International Conference on Digital Forensics (DF), Jan 2014, Vienna, Austria. Springer, IFIP Advances in Information and Communication Technology, AICT-433, pp.185-205, 2014, Advances in Digital Forensics X. 〈10.1007/978-3-662-44952-3_13〉. 〈hal-01393771〉
