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  Dr Andrea Nini  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

About the Project

Authorship analysis, sometimes also called authorship attribution or authorship identification, is the task of determining who wrote a document based on the author’s use of language. This problem is often encountered in situations in which a document is evidence in a forensic case, for example when the authorship of a text like a threatening letter is crucial for investigations. More specifically, this is a task that is often needed by practitioners of forensic linguistics, a relatively new field that concerns the application of linguistics to forensic problems (Coulthard et al. 2017).

Authorship analysis has been extensively studied from a computational perspective (e.g. Juola 2008, Stamatatos 2009, Tyo et al. 2022). However, there is still limited research on the use of language models to solve this problem.

The use of language models to solve the authorship analysis task is compatible with the framework introduced by Nini (2023), where authorship analysis is seen as the task of recognising whose grammar produced a certain text. The process of grammar induction can be thought of as a language modelling problem and the objective of this project is precisely to understand the potential and limitations of Large Language Models when used for grammar induction.

Entry Requirements

Academic:

Applicants must have minimum qualifications of a good Upper Second-Class honours Bachelor's degree (or international equivalent) in a relevant discipline, and a UK Master's degree with an overall average of 65% or higher, with a minimum of 65% in the dissertation and with no mark below 55% (or its international equivalent) in a related subject.

Due to variations in the grading structures of international institutions, higher results may be required than stated here. 

The successful applicant is expected to have a degree in Computer Science, preferably with experience of working with language models.

English Language:

Applicants whose first language is not English require one of the following:

  • IELTS test minimum scores - 7 overall, 7 writing, 6.5 other sections
  • TOEFL (internet-based) test minimum scores - 103 overall, 28 writing, 25 other sections
  • Pearson Test of English (PTE Academic/Academic UKVI) minimum scores - 76 overall, 76 writing, 70 other sections

Application procedure

The application deadline will be Midnight (BST) on 30/06/2024.

Apply online

Please ensure you include all required supporting documents at the time of submission, as incomplete applications may not be considered. A Personal Statement is NOT required to be submitted. You should select 'Supporting Statement is not required for this programme'.

The application must include:

  • two academic references;
  • photocopies of degree certificates if the degree has already been awarded and official transcripts of previous and current study;
  • research proposal;
  • a copy of your passport (if you will need a visa to study here);

Interview requirements

The University requires an interview for all applicants to whom we consider making an offer.

Interviews will be conducted by two academics, usually the proposed main supervisor and the subject PGR Director (or an assigned representative).

The interview can be either face-to-face or via conference call or email.

The interview serves several purposes, allowing us to:

  • get a better picture of your ability to carry out the proposed doctoral project than the research proposal on its own;
  • tell you what the proposed supervisor(s) can bring to the project;
  • discuss with you directly any potential problems with the practical aspects of your studies and explore solutions together.

Further information

If you have any questions or would like to discuss this further, please contact Andrea Nini ([Email Address Removed])

Computer Science (8) Linguistics & Classics (23)

Funding Notes

This project is available to all self-funded applicants, both international and home.

References

Coulthard, M., Johnson, A. and Wright, D. (2017) An Introduction to Forensic Linguistics, London, Routledge.
Juola, P. (2008) Authorship Attribution, Foundations and Trends in Information Retrieval, 1(3), pp. 233–334.
Nini, A. (2023) A Theory of Linguistic Individuality for Authorship Analysis (Elements in Forensic Linguistics). Cambridge, UK: Cambridge University Press.
Stamatatos, E. (2009) A survey of modern authorship attribution methods, Journal of the American Society for Information Science and Technology, 60(3), pp. 538–556.
Tyo, J., Bhuwan, D. & Lipton, Z. C. (2022) On the State of the Art in Authorship Attribution and Authorship Verification. arXiv. http://arxiv.org/abs/2209.06869. (29 December, 2022).
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