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Article published In:
International Journal of Corpus Linguistics
Vol. 22:2 (2017) ► pp.212–241

Using word n-grams to identify authors and idiolects

A corpus approach to a forensic linguistic problem

| Nottingham Trent University
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: forensic linguistics, idiolect, authorship attribution, entrenchment, Enron
Article outline
  • 1.The linguistic individual, corpora and forensic linguistics
  • 2.Word strings as features in authorship analysis
    • 2.1Word strings, routine and the individual
    • 2.2Empirical evidence for idiolectal word strings
    • 2.3‘Word n-grams’ in this study
  • 3.Methodology
    • 3.1The Enron Email Corpus
    • 3.2The authorship attribution experiment
  • 4.Attribution results
    • 4.1Effect of sample size
    • 4.2Performance of different n-gram lengths
    • 4.3Performance across authors
  • 5.Identifying idiolectal word n-grams
  • 6.Conclusions and implications
  • Acknowledgements
  • References
Published online: 16 October 2017
DOI logo
https://doi.org/10.1075/ijcl.22.2.03wri
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