Abstract
This paper describes how social identity group "fingerprints" can be extracted from a document collection by applying topic analysis methods in a novel way. The results of document classification experiments suggest that these group-level attributes provide better predictions of group affiliation than document-level attributes. Applications of this method for forensic authorship analysis are also discussed. © 2008 Springer-Verlag Berlin Heidelberg.
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Booker, L. B. (2008). Finding identity group “fingerprints” in documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5158 LNCS, pp. 113–121). https://doi.org/10.1007/978-3-540-85303-9_11
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