A Systemic Functional Approach To Automated Authorship Analysis
Shlomo Argamon, Moshe Koppel · bepress Legal Repository · 2013
Attribution of anonymous texts, if not based on factors external to the text (such as paper and ink type or document provenance, as used in forensic document examination), is largely, if not entirely, based on considerations of language style. We will consider here the question of how to best deconstruct a text into quantitative features for purposes of stylistic discrimination. Two key considerations inform our analysis. First, such features should support accurate classification by automated methods. Second, and no less importantly, such features should enable a clear explanation of the stylistic difference between stylistic categories (read: authors) and why a disputed text appears more likely to fall into one or another category. The latter consideration is particularly important when a non-expert, such as a judge or jury, must evaluate the results and reliability of the analysis. We sketch here a computationally tractable formulation of linguistically and stylistically well-motivated features we have developed that permits text classification based on specific variation in choice of non-referential meanings. The system produces meaningful information about the stylistic distinctions being analyzed, which can be used for interpretative and forensic purposes. We will explain our methodology and then use it as a case study for what any such methodology should provide.