Genre in Non-Traditional Authorship Attribution Studies
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A01=Joseph Rudman
advanced authorship attribution techniques
Author_Joseph Rudman
authorship attribution
Category=CFG
Category=DDA
Category=DSA
computational text analysis
cross-domain stylistic analysis
digital humanities research
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eq_biography-true-stories
eq_dictionaries-language-reference
eq_isMigrated=1
eq_isMigrated=2
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eq_nobargain
eq_non-fiction
eq_poetry
experimental design methods
Forensic linguistics
genre
Large Language Models
legal language identification
linguistic feature extraction
Shakespeare
stylistics
Product details
- ISBN 9781041133995
- Weight: 670g
- Dimensions: 152 x 229mm
- Publication Date: 20 Apr 2026
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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This timely monograph explores the critical, yet often overlooked, role of genre in non-traditional authorship attribution studies. Drawing from linguistics, rhetoric, stylistics, forensic linguistics, and computational methods –including large language models (LLMs) – this book argues that genre must be treated as a central variable in any credible attribution analysis. Across domains from Shakespearean drama to courtroom linguistics, the book highlights how failing to control for genre risks undermines both results and credibility. It challenges the extremes of current thinking – whether genre dominates authorship or is eclipsed by it – by examining the vast and complex gray area between these poles. With case studies, critical commentary, and a detailed appendix cataloging over 120 stylistic markers across genres and authors, this work provides a robust resource for scholars, digital humanists, forensic linguists, and anyone invested in the integrity of authorship studies. It also offers an accessible introduction to the promises and pitfalls of LLMs in this evolving field. This volume is essential reading for both practitioners and consumers of attribution research.
Joseph Rudman currently serves as a Special Faculty Member in the English Department at Carnegie Mellon University.
