Eileen Fitzpatrick, Joan Bachenko, Tommaso Fornaciari

eBook, PDF

Automatic Detection of Verbal Deception (eBook, PDF)

Beschreibung

The attempt to spot deception through its correlates in human behavior has a long history. Until recently, these efforts have concentrated on identifying individual "cues" that might occur with deception. However, with the advent of computational means to analyze language and other human behavior, we now have the ability to determine whether there are consistent clusters of differences in behavior that might be associated with a false statement as opposed to a true one. While its focus is on verbal behavior, this book describes a range of behaviors-physiological, gestural as well as verbal-that have been proposed as indicators of deception. An overview of the primary psychological and cognitive theories that have been offered as explanations of deceptive behaviors gives context for the description of specific behaviors. The book also addresses the differences between data collected in a laboratory and "real-world" data with respect to the emotional and cognitive state of the liar. It discusses sources of real-world data and problematic issues in its collection and identifies the primary areas in which applied studies based on real-world data are critical, including police, security, border crossing, customs, and asylum interviews; congressional hearings; financial reporting; legal depositions; human resource evaluation; predatory communications that include Internet scams, identity theft, and fraud; and false product reviews. Having established the background, this book concentrates on computational analyses of deceptive verbal behavior that have enabled the field of deception studies to move from individual cues to overall differences in behavior. The computational work is organized around the features used for classification from ¿¿¿¿-gram through syntax to predicate-argument and rhetorical structure. The book concludes with a set of open questions that the computational work has generated.

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Autor

Eileen Fitzpatrick is a professor in the Linguistics Department at Montclair State University. Previously she was a member of the technical staff at AT&T Bell Laboratories in Murray Hill, NJ. She has been the principal investigator on several Department of Defense contracts involving the annotation of narrative data and modeling of classifiers to predict deception. She is the author of papers on corpus building and modeling of deceptive narrative. Dr. Fitzpatrick served for six years on the Institutional Review Board at Montclair State, where she dealt with the privacy constraints on the collection of real world and laboratory data.

Joan Bachenko is president of Linguistech LLC and serves as adjunct faculty in Linguistics at Montclair State University. Previously she worked on NLP and speech technology at the Naval Research Laboratory in Washington DC and AT&T Bell Laboratories in Murray Hill, NJ. She left Bell Laboratories to co-found Linguistic Technologies, Inc. (LTI) inMinnesota, where she directed R&D projects on speech recognition systems for medical applications and served on the graduate faculty of the University of Minnesota. After the sale of LTI she began her current work on deception. Dr. Bachenko holds three software patents and has published papers on speech, parsing and deceptive language.

Tommaso Fornaciari is an Investigative Psychologist with the Italian National Police. Since obtaining his PhD at the University of Trento, he has carried out research activities in forensic linguistics, publishing studies in which computational methods are employed with the aim of detecting deception in text and in transcripts of spoken language from criminal proceedings. He presently works at the Department of Public Security of the Italian Ministry of the Interior, engaged in research and technological innovation for public security. Prior to that, he worked at the Forensic Science Police Service, where he dealt with criminal analysis, mostly regarding violent murders.

Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 101
• Erscheinungstermin: 31. Mai 2022
• Englisch
• ISBN-13: 9783031021589
• Artikelnr.: 64124517