A Systemic Functional Approach to Automated Authorship Analysis

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 nonexpert, such as a judge or jury, must evaluate the results and reliability of the analysis. We start from the intuitive notion that style is indicated in a text by those features of the text that indicate the author’s choice of one mode of expression from among a set of equivalent modes for a given content. There are many ways in which such choices manifest themselves in a text. Specific words and phrases may be chosen more frequently by certain authors than others, such as the phrase “cool-headed logician” favored by the Unabomber. Some authors may habitually use certain syntactic