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Breaking the Closed-World Assumption in Stylometric Authorship Attribution

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.
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Ariel Stolerman, Rebekah Overdorf, Sadia Afroz, Rachel Greenstadt. Breaking the Closed-World Assumption in Stylometric Authorship Attribution. 10th IFIP International Conference on Digital Forensics (DF), Jan 2014, Vienna, Austria. pp.185-205, ⟨10.1007/978-3-662-44952-3_13⟩. ⟨hal-01393771⟩



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