Abstract
The increasing volume of digital linguistic evidence and the expansion of virtual communicative spaces demand forensic linguistic tools that are both methodologically rigorous and accessible to a wider range of users, including legal practitioners. This paper introduces a bespoke, web-based authorship analysis tool designed to identify and visualize key textual patterns across questioned and known datasets. Operating through an intuitive graphical user interface, the tool offers an accessible alternative to command-line methods, expanding the reach of computational forensic linguistics to non-technical users. The tool integrates two core functionalities: (1) automated identification and comparison of shared n-grams, particularly bigrams and trigrams, within and between datasets, and (2) Key Word in Context (KWIC) exploration to support the interpretation of overlapping or distinctive lexical patterns. By combining these capabilities, the system enables both confirmatory and exploratory analysis of linguistic evidence, supporting investigations where authorship is contested or where stylistic consistency must be assessed. It has applications across the three domains of forensic linguistics: language as evidence, interaction in legal settings, and language of the law. In addition to its methodological contributions, the paper addresses key challenges in forensic semiotics: subjectivity, reproducibility, and transparency. It shows how computational approaches can mitigate the “subjectivity effect” by offering replicable, data-driven analyses of linguistic behaviour. Courtroom admissibility is also supported by producing clear, step-by-step analytical records and exportable logs that document each analytic operation. Our contribution aligns with the aims of computational forensic linguistics to enhance the interpretive rigour and evidentiary validity of linguistic analyses.
| Original language | English |
|---|---|
| Number of pages | 27 |
| Journal | International Journal for the Semiotics of Law |
| Early online date | 10 Jun 2026 |
| DOIs | |
| Publication status | E-pub ahead of print - 10 Jun 2026 |
Bibliographical note
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