Rank-Turbulence Delta and Interpretable Approaches to Stylometric Delta Metrics 文章

ArXiv CS.CL2026-05-27NEWSen作者: Dmitry Pronin, Evgeny Kazartsev

摘要

arXiv:2604.19499v4 Announce Type: replace Abstract: This article introduces two new measures for authorship attribution - Rank-Turbulence Delta and Jensen-Shannon Delta - which generalise Burrows's classical Delta by applying distance functions designed for probabilistic distributions. We first set out the theoretical basis of the measures, contrasting centred and uncentred z-scoring of word-frequency vectors and re-casting the uncentred vectors as probability distributions. Building on this representation, we develop a token-level decomposition that renders every Delta distance numerically interpretable, thereby facilitating close reading and the validation of results. The effectiveness of the methods is assessed on four literary corpora in English, German, French and Russian.