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Using word n-grams to identify authors and idiolects

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Forensic authorship attribution is concerned with identifying the writers of anonymous criminal documents. Over the last twenty years, computer scientists have developed a wide range of statistical procedures using a number of different linguistic features to measure similarity between texts. However, much of this work is not of practical use to forensic linguists who need to explain in reports or in court why a particular method of identifying potential authors works. This paper sets out to address this problem using a corpus linguistic approach and the 176-author 2.5 million-word Enron Email Corpus. Drawing on literature positing the idiolectal nature of collocations, phrases and word sequences, this paper tests the accuracy of word n-grams in identifying the authors of anonymised email samples. Moving beyond the statistical analysis, the usage-based concept of entrenchment is offered as a means by which to account for the recurring and distinctive production of idiolectal word n-grams.

Keywords: Enron; authorship attribution; entrenchment; forensic linguistics; idiolect

Document Type: Research Article

Publication date: September 22, 2017

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