Automatic Detection of Verbal Deception (Record no. 85485)

000 -LEADER
fixed length control field 04294nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-031-02158-9
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730164241.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2015 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031021589
-- 978-3-031-02158-9
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Fitzpatrick, Eileen.
245 10 - TITLE STATEMENT
Title Automatic Detection of Verbal Deception
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2015.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVII, 101 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Human Language Technologies,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Preface -- Acknowledgments -- Introduction -- The Background Literature on Behavioral Cues to Deception -- Data Sources -- The Language of Deception: Computational Approaches -- Open Questions -- Bibliography -- Authors' Biographies.
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Bachenko, Joan.
700 1# - AUTHOR 2
Author 2 Fornaciari, Tommaso.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-02158-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
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-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2015.
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-- computer
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-- rdamedia
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-- online resource
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-- text file
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Natural language processing (Computer science).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational linguistics.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Natural Language Processing (NLP).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Linguistics.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1947-4059
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-- ZDB-2-SXSC

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