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Can Three Pronouns Discriminate Identity in Writing?

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Data and Decision Sciences in Action

Part of the book series: Lecture Notes in Management and Industrial Engineering ((LNMIE))

Abstract

In a study of three female and two male contemporary authors, five thousand words from each was obtained by accessing 30 freely available news articles, Web articles, personal blog posts, book extracts, and oration transcripts on the Internet. The data was anonymised to remove identity. All 25,000 words were aggregated across the 30 articles by word frequency and 29 personal pronouns extracted and normalised by sample size. Using logistic regression, each sample was tested to determine if it were possible to identify the author’s gender using a subset of personal pronouns. The study found that it is possible to identify gender with 90% accuracy using the three pronouns ‘my’, ‘her’, and ‘its. The technique was tested against six independent samples with 84% accuracy and could support the identification of adversaries on the Internet or in a theatre of war.

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Acknowledgements

This work formed part of a Master of Philosophy thesis through the University of New South Wales [4] and acknowledges the support of two former supervisors, Robert Stocker and Edward Lewis. We thank Andrew Gill for his help with the logistic regression programming within the R environment. This research is supported by the Defence Science Technology Group.

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Authors and Affiliations

  1. Joint and Operations Analysis Division, Defence Science Technology Group, Edinburgh, Australia

    David Kernot

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  1. David Kernot
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Correspondence to David Kernot .

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Editors and Affiliations

  1. School of Engineering and Information Technology, University of New South Wales, Canberra, Aust Capital Terr, Australia

    Ruhul Sarker

  2. School of Engineering and Information Technology, University of New South Wales, Canberra, Aust Capital Terr, Australia

    Hussein A. Abbass

  3. Data 61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Melbourne, Victoria, Australia

    Simon Dunstall

  4. Data 61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Melbourne, Victoria, Australia

    Philip Kilby

  5. Strategic Capability Analysis Department, Defence Science and Technology Group, Canberra, Aust Capital Terr, Australia

    Richard Davis

  6. Department of Defence, War Research Centre, Canberra, Aust Capital Terr, Australia

    Leon Young

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Kernot, D. (2018). Can Three Pronouns Discriminate Identity in Writing?. In: Sarker, R., Abbass, H., Dunstall, S., Kilby, P., Davis, R., Young, L. (eds) Data and Decision Sciences in Action. Lecture Notes in Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-55914-8_29

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  • DOI: https://doi.org/10.1007/978-3-319-55914-8_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55913-1

  • Online ISBN: 978-3-319-55914-8

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