Best Practices and Admissibility of Forensic Author Identification

Forensic linguistics provides answers to four categories of inquiry in investigative and legal settings: (i) identification of author, language, or speaker; (ii) intertextuality, or the relationship between texts; (iii) text-typing or classification of text types such as threats, suicide notes, or predatory chat; and (iv) linguistic profiling to assess the author’s dialect, native language, age, gender, and educational level. This article discusses author identification in relation to linguistics, research, and admissibility as evidence in U.S. courts. Federal and states courts in the United States have undertaken three main approaches in determining whether to admit, partially admit, or exclude forensic authorship identification evidence. These three approaches are forensic computational linguistics, forensic stylistics, and stylometric computing. Each has a distinct origin. Forensic computational linguistics developed out of linguistic theory and computational linguistics. Forensic stylistics developed out of traditional forensic handwriting identification. The stylometric computing approach developed out of both literary authorship identification and machine-learning-based text classification.