Automatic Detection Of Verbal Deception

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Automatic Detection of Verbal Deception

Author : Eileen Fitzpatrick,Joan Bachenko,Tommaso Fornaciari
Publisher : Springer Nature
Page : 101 pages
File Size : 54,9 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031021589

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Automatic Detection of Verbal Deception by Eileen Fitzpatrick,Joan Bachenko,Tommaso Fornaciari Pdf

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.

The Palgrave Handbook of Deceptive Communication

Author : Tony Docan-Morgan
Publisher : Springer
Page : 1039 pages
File Size : 53,8 Mb
Release : 2019-04-29
Category : Psychology
ISBN : 9783319963341

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The Palgrave Handbook of Deceptive Communication by Tony Docan-Morgan Pdf

Deception and truth-telling weave through the fabric of nearly all human interactions and every communication context. The Palgrave Handbook of Deceptive Communication unravels the topic of lying and deception in human communication, offering an interdisciplinary and comprehensive examination of the field, presenting original research, and offering direction for future investigation and application. Highly prominent and emerging deception scholars from around the world investigate the myriad forms of deceptive behavior, cross-cultural perspectives on deceit, moral dimensions of deceptive communication, theoretical approaches to the study of deception, and strategies for detecting and deterring deceit. Truth-telling, lies, and the many grey areas in-between are explored in the contexts of identity formation, interpersonal relationships, groups and organizations, social and mass media, marketing, advertising, law enforcement interrogations, court, politics, and propaganda. This handbook is designed for advanced undergraduate and graduate students, academics, researchers, practitioners, and anyone interested in the pervasive nature of truth, deception, and ethics in the modern world.

Automatic Text Simplification

Author : Horacio Saggion
Publisher : Springer Nature
Page : 121 pages
File Size : 41,6 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031021664

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Automatic Text Simplification by Horacio Saggion Pdf

Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences. However, the way in which a text is written—its vocabulary, its syntax—can be difficult to read and understand for many people, especially those with poor literacy, cognitive or linguistic impairment, or those with limited knowledge of the language of the text. Texts containing uncommon words or long and complicated sentences can be difficult to read and understand by people as well as difficult to analyze by machines. Automatic text simplification is the process of transforming a text into another text which, ideally conveying the same message, will be easier to read and understand by a broader audience. The process usually involves the replacement of difficult or unknown phrases with simpler equivalents and the transformation of long and syntactically complex sentences into shorter and less complex ones. Automatic text simplification, a research topic which started 20 years ago, now has taken on a central role in natural language processing research not only because of the interesting challenges it posesses but also because of its social implications. This book presents past and current research in text simplification, exploring key issues including automatic readability assessment, lexical simplification, and syntactic simplification. It also provides a detailed account of machine learning techniques currently used in simplification, describes full systems designed for specific languages and target audiences, and offers available resources for research and development together with text simplification evaluation techniques.

Computer Vision and Image Processing

Author : Neeta Nain,Santosh Kumar Vipparthi,Balasubramanian Raman
Publisher : Springer Nature
Page : 530 pages
File Size : 42,5 Mb
Release : 2020-03-28
Category : Computers
ISBN : 9789811540189

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Computer Vision and Image Processing by Neeta Nain,Santosh Kumar Vipparthi,Balasubramanian Raman Pdf

This two-volume set (CCIS 1147, CCIS 1148) constitutes the refereed proceedings of the 4th International Conference on Computer Vision and Image Processing. held in Jaipur, India, in September 2019. The 73 full papers and 10 short papers were carefully reviewed and selected from 202 submissions. The papers are organized by the topical headings in two parts. Part I: Biometrics; Computer Forensic; Computer Vision; Dimension Reduction; Healthcare Information Systems; Image Processing; Image segmentation; Information Retrieval; Instance based learning; Machine Learning.Part II: ​Neural Network; Object Detection; Object Recognition; Online Handwriting Recognition; Optical Character Recognition; Security and Privacy; Unsupervised Clustering.

Introduction to Cyberdeception

Author : Neil C. Rowe,Julian Rrushi
Publisher : Springer
Page : 334 pages
File Size : 40,7 Mb
Release : 2016-09-23
Category : Computers
ISBN : 9783319411873

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Introduction to Cyberdeception by Neil C. Rowe,Julian Rrushi Pdf

This book is an introduction to both offensive and defensive techniques of cyberdeception. Unlike most books on cyberdeception, this book focuses on methods rather than detection. It treats cyberdeception techniques that are current, novel, and practical, and that go well beyond traditional honeypots. It contains features friendly for classroom use: (1) minimal use of programming details and mathematics, (2) modular chapters that can be covered in many orders, (3) exercises with each chapter, and (4) an extensive reference list.Cyberattacks have grown serious enough that understanding and using deception is essential to safe operation in cyberspace. The deception techniques covered are impersonation, delays, fakes, camouflage, false excuses, and social engineering. Special attention is devoted to cyberdeception in industrial control systems and within operating systems. This material is supported by a detailed discussion of how to plan deceptions and calculate their detectability and effectiveness. Some of the chapters provide further technical details of specific deception techniques and their application. Cyberdeception can be conducted ethically and efficiently when necessary by following a few basic principles. This book is intended for advanced undergraduate students and graduate students, as well as computer professionals learning on their own. It will be especially useful for anyone who helps run important and essential computer systems such as critical-infrastructure and military systems.

Detecting Lies and Deceit

Author : Aldert Vrij
Publisher : John Wiley & Sons
Page : 519 pages
File Size : 40,5 Mb
Release : 2008-02-19
Category : Psychology
ISBN : 9780470516256

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Detecting Lies and Deceit by Aldert Vrij Pdf

Why do people lie? Do gender and personality differences affect how people lie? How can lies be detected? Detecting Lies and Deceit provides the most comprehensive review of deception to date. This revised edition provides an up-to-date account of deception research and discusses the working and efficacy of the most commonly used lie detection tools, including: Behaviour Analysis Interview Statement Validity Assessment Reality Monitoring Scientific Content Analysis Several different polygraph tests Voice Stress Analysis Thermal Imaging EEG-P300 Functional Magnetic Resonance Imaging (fMRI) All three aspects of deception are covered: nonverbal cues, speech and written statement analysis and (neuro)physiological responses. The most common errors in lie detection are discussed and practical guidelines are provided to help professionals improve their lie detection skills. Detecting Lies and Deceit is a must-have resource for students, academics and professionals in psychology, criminology, policing and law.

A Practical Guide to Sentiment Analysis

Author : Erik Cambria,Dipankar Das,Sivaji Bandyopadhyay,Antonio Feraco
Publisher : Springer
Page : 199 pages
File Size : 45,9 Mb
Release : 2017-04-07
Category : Medical
ISBN : 9783319553948

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A Practical Guide to Sentiment Analysis by Erik Cambria,Dipankar Das,Sivaji Bandyopadhyay,Antonio Feraco Pdf

Sentiment analysis research has been started long back and recently it is one of the demanding research topics. Research activities on Sentiment Analysis in natural language texts and other media are gaining ground with full swing. But, till date, no concise set of factors has been yet defined that really affects how writers’ sentiment i.e., broadly human sentiment is expressed, perceived, recognized, processed, and interpreted in natural languages. The existing reported solutions or the available systems are still far from perfect or fail to meet the satisfaction level of the end users. The reasons may be that there are dozens of conceptual rules that govern sentiment and even there are possibly unlimited clues that can convey these concepts from realization to practical implementation. Therefore, the main aim of this book is to provide a feasible research platform to our ambitious researchers towards developing the practical solutions that will be indeed beneficial for our society, business and future researches as well.

Detecting Lies and Deceit

Author : Aldert Vrij
Publisher : Wiley-Blackwell
Page : 288 pages
File Size : 47,5 Mb
Release : 2000-05-25
Category : Law
ISBN : UOM:39015042934250

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Detecting Lies and Deceit by Aldert Vrij Pdf

Why do people lie, and how can lies be detected? There is now a substantial psychological literature relating to these fundamental questions, and this book reviews the relevant knowledge in detail, before focusing on guidelines for best practice in detecting deception. Psychological research is now available on individual differences in lying behaviour (gender differences, age differences and personality). There is also interesting research evidence of the ways in which deception is reflected both in real objective non-verbal behaviour and also in the perceived non-verbal cues which can help or mislead the observer in detecting deception. Although the book does include a major survey of the physiological aspects of deception and the polygraph as a method of detection, it also includes a thorough review of current knowledge of content analysis and validity assessment of speech and written statements. The book ends by discussing how professionals can improve lie detection by focusing on key aspects of the behaviour of the liar and by awareness and control of their own behaviour. Covers all three aspects of deception?non-verbal cues, speech and written statement analysis, and physiological responses Focuses on the behaviour and perceptions of the observer which can hinder the process of detection Based on the author?s expert review of the research and evidence, and on his practical experience and connections with several police forces "Without doubt, this book is the most important contribution to research and practice in lie detection to be published in years. For the first time research about verbal, nonverbal and physiological correlates of truth telling and deception are reviewed comprehensively in one text. This book will benefit those who have to decide whether people are telling the truth or lying, because it both reviews contemporary research and provides practical guidelines." Frans Willem Winkel, Free University of Amsterdam President EAPL (European Association of Psychology and Law) This book is aimed at students, academics and professionals in psychology, criminology, policing and law.

Misinformation and Disinformation

Author : Victoria L. Rubin
Publisher : Springer Nature
Page : 305 pages
File Size : 42,7 Mb
Release : 2022-06-14
Category : Technology & Engineering
ISBN : 9783030956561

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Misinformation and Disinformation by Victoria L. Rubin Pdf

This book, geared towards both students and professionals, examines the synthesis of artificial intelligence (AI) and psychology in detecting mis-/disinformation in digital media content, and suggests practical means to intervene and curtail this current global ‘infodemic’. This interdisciplinary book explores technological, psychological, philosophical, and linguistic insights into the nature of truth and deception, trust and credibility, cognitive biases and logical fallacies and how, through AI and human intervention, content users can be alerted to the presence of deception. The author investigates how AI can mimic the procedures and know-hows of humans, showing how AI can help spot fakes and how AI tools can work to debunk rumors and fact-check. The book describes how AI detection systems work and how they fit with broader societal and individual concerns. Each chapter focuses attention on key concepts and their inter-connection. The first part of the book seeks theoretical footing to understand our interactions with new information and reviews relevant empirical findings in behavioral sciences. The second part is about applied knowledge. The author looks at several known practices that guard us against deception, and provides several real-world examples of manipulative persuasive techniques in advertising, political propaganda, and public relations. She provides links to the downloadable executable files to three AI applications (clickbait, satire, and falsehood detectors) via LiT.RL GitHub, an open access repository. The book is useful to students and professionals studying AI and media studies as well as library and information professionals. Examines how artificial intelligence (AI) and psychology can aid in detecting mis-/disinformation and the language of deceit in digital media content; Suggests practical computational means to intervene and curtail the global ‘infodemic’ of fake news; Presents how AI can sift, sort, and shuffle digital content, to reduce the amount of content needed to be reviewed by humans.

Language as Evidence

Author : Victoria Guillén-Nieto,Dieter Stein
Publisher : Springer Nature
Page : 471 pages
File Size : 50,5 Mb
Release : 2022-02-09
Category : Language Arts & Disciplines
ISBN : 9783030843304

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Language as Evidence by Victoria Guillén-Nieto,Dieter Stein Pdf

This edited book provides a comprehensive survey of the modern state of the art in forensic linguistics. Part I of the book focuses on the role of the linguist as an expert witness in common law and civil law jurisdictions, the relation of expert witnesses and lawyers, ethics standards, and courtroom interaction. Part II deals with some of the major areas of expertise of forensic linguistics as the scientific study of language as evidence, namely authorship identification, speaker identification, text authentication, deception and lie detection, plagiarism detection, and cyber language crimes. This book is intended to be used as a reference for academics, students and practitioners of Linguistics, Forensic Linguistics, Law, Criminology, and Forensic Psychology, among other disciplines.

Automated Essay Scoring

Author : Beata Beigman Klebanov,Nitin Madnani
Publisher : Springer Nature
Page : 294 pages
File Size : 45,5 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031021824

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Automated Essay Scoring by Beata Beigman Klebanov,Nitin Madnani Pdf

This book discusses the state of the art of automated essay scoring, its challenges and its potential. One of the earliest applications of artificial intelligence to language data (along with machine translation and speech recognition), automated essay scoring has evolved to become both a revenue-generating industry and a vast field of research, with many subfields and connections to other NLP tasks. In this book, we review the developments in this field against the backdrop of Elias Page's seminal 1966 paper titled "The Imminence of Grading Essays by Computer." Part 1 establishes what automated essay scoring is about, why it exists, where the technology stands, and what are some of the main issues. In Part 2, the book presents guided exercises to illustrate how one would go about building and evaluating a simple automated scoring system, while Part 3 offers readers a survey of the literature on different types of scoring models, the aspects of essay quality studied in prior research, and the implementation and evaluation of a scoring engine. Part 4 offers a broader view of the field inclusive of some neighboring areas, and Part \ref{part5} closes with summary and discussion. This book grew out of a week-long course on automated evaluation of language production at the North American Summer School for Logic, Language, and Information (NASSLLI), attended by advanced undergraduates and early-stage graduate students from a variety of disciplines. Teachers of natural language processing, in particular, will find that the book offers a useful foundation for a supplemental module on automated scoring. Professionals and students in linguistics, applied linguistics, educational technology, and other related disciplines will also find the material here useful.

Natural Language Processing for Social Media

Author : Atefeh Farzindar
Publisher : Springer Nature
Page : 158 pages
File Size : 51,5 Mb
Release : 2015-08-31
Category : Computers
ISBN : 9783031021572

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Natural Language Processing for Social Media by Atefeh Farzindar Pdf

In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on Natural Language Processing (NLP) tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, business intelligence, industry, marketing, and security and defense. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, and social networking.

Statistical Significance Testing for Natural Language Processing

Author : Rotem Dror
Publisher : Springer Nature
Page : 98 pages
File Size : 55,6 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031021749

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Statistical Significance Testing for Natural Language Processing by Rotem Dror Pdf

Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms. In fact, in the last decade, it has become rare to see an NLP paper, particularly one that proposes a new algorithm, that does not include extensive experimental analysis, and the number of involved tasks, datasets, domains, and languages is constantly growing. This emphasis on empirical results highlights the role of statistical significance testing in NLP research: If we, as a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental. The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.

Statistical Methods for Annotation Analysis

Author : Silviu Paun,Ron Artstein
Publisher : Springer Nature
Page : 208 pages
File Size : 47,5 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031037634

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Statistical Methods for Annotation Analysis by Silviu Paun,Ron Artstein Pdf

Labelling data is one of the most fundamental activities in science, and has underpinned practice, particularly in medicine, for decades, as well as research in corpus linguistics since at least the development of the Brown corpus. With the shift towards Machine Learning in Artificial Intelligence (AI), the creation of datasets to be used for training and evaluating AI systems, also known in AI as corpora, has become a central activity in the field as well. Early AI datasets were created on an ad-hoc basis to tackle specific problems. As larger and more reusable datasets were created, requiring greater investment, the need for a more systematic approach to dataset creation arose to ensure increased quality. A range of statistical methods were adopted, often but not exclusively from the medical sciences, to ensure that the labels used were not subjective, or to choose among different labels provided by the coders. A wide variety of such methods is now in regular use. This book is meant to provide a survey of the most widely used among these statistical methods supporting annotation practice. As far as the authors know, this is the first book attempting to cover the two families of methods in wider use. The first family of methods is concerned with the development of labelling schemes and, in particular, ensuring that such schemes are such that sufficient agreement can be observed among the coders. The second family includes methods developed to analyze the output of coders once the scheme has been agreed upon, particularly although not exclusively to identify the most likely label for an item among those provided by the coders. The focus of this book is primarily on Natural Language Processing, the area of AI devoted to the development of models of language interpretation and production, but many if not most of the methods discussed here are also applicable to other areas of AI, or indeed, to other areas of Data Science.

Natural Language Processing for Social Media, Third Edition

Author : Anna Atefeh Farzindar,Diana Inkpen
Publisher : Springer Nature
Page : 193 pages
File Size : 48,6 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031021756

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Natural Language Processing for Social Media, Third Edition by Anna Atefeh Farzindar,Diana Inkpen Pdf

In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms that extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. This book will discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts, and it shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, and business intelligence. The book further covers the existing evaluation metrics for NLP and social media applications and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF). In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data.