Detecting hidden authors in political texts using writing style analysis

Detecting Authorship in Political Texts with Inductive Stylometry

Computation and Language

Summary

Political texts like speeches and tweets often have multiple people involved in writing, not just the person they’re attributed to. This paper shows how analyzing patterns in writing style, even small details like sequences of characters, can help identify different hidden authors in these texts. The authors test their method on different types of political writing in English and Hungarian and find it can separate staff members’ contributions in some cases, like legal documents or scripted speeches. However, it does not always distinguish individual speechwriters when many work on similar texts. Their approach helps understand who actually shapes political communication behind the scenes.

StylometryAuthorship attributionPolitical communicationCharacter n-gramsDimensionality reductionUMAPBurrows' DeltaLatent authorshipSpeechwritingText analysis

Authors

Gennadii Iakovlev, Levente Littvay

Abstract

Political texts are rarely authored by the nominal speaker alone. Tweets, speeches, reports, and official statements are drafted, edited, or harmonized by staff, yet political science has paid limited attention to the stylistic traces these hidden authors leave behind. This paper develops and stress-tests an inductive stylometric approach for recovering latent authorship structure in political communication, combining character 3-gram features with UMAP dimensionality reduction, and Burrows' Delta. We apply the approach to six corpora that vary in length (from tweets to long documents), in mode (written and oral), and in language (English and Hungarian). The approach recovers near-disjoint analyst fingerprints in formal legal prose in both languages, sorts a politician's tweets into validated subsets while uncovering additional insights, and distinguishes scripted from improvised speech. It fails, however, to resolve individual speechwriters within scripted corpora. Frequency-based stylometry is thus a powerful tool that, depending on authorial signal strength and institutional editing, can uncover authorship traces relevant to legislative studies, political communication, and policy research.