Implementing a novel method for identifying idiolectal co-selections, and taking the UNABOM investigation as a case study, this Pivot evaluates the effectiveness and reliability of using the web for forensic purposes.
Implementing a novel method for identifying idiolectal co-selections, and taking the UNABOM investigation as a case study, this Pivot evaluates the effectiveness and reliability of using the web for forensic purposes.
Samuel Larner is a Lecturer in Forensic Linguistics at the University of Central Lancashire, UK. His research interests are primarily in forensic linguistics, specifically authorship analysis and deception detection. Samuel is a Fellow of the Higher Education Academy and teaches both undergraduate and postgraduate modules in linguistics, contributing in particular to an innovative and interdisciplinary MSc in Emotions, Credibility and Deception.
Inhaltsangabe
1. Introduction: The UNABOM Investigation 2. The Web as Corpus and Authorship Attribution 3. Attributing Documents to Unknown Authors Using Idiolectal Co-selection and the Web 4. Attributing Documents to Candidate Authors Using Idiolectal Co-Selection and the Web 5. The Suitability of the Web for Producing Forensic Evidence ? ?
1. Introduction: The UNABOM Investigation 2. The Web as Corpus and Authorship Attribution 3. Attributing Documents to Unknown Authors Using Idiolectal Co-selection and the Web 4. Attributing Documents to Candidate Authors Using Idiolectal Co-Selection and the Web 5. The Suitability of the Web for Producing Forensic Evidence ? ?
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