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This paper aims to systematically compare the textbook‐based criminal justice and psychological literatures on detecting deception in field settings to determine the accuracy of the criminal justice literature in this area.

A total of 18 criminal justice textbooks covering detecting deception were systematically reviewed and coded. The alleged indicators of deception were then compared with the psychological literature on the valid indicators of deception.

Many criminal justice textbooks on interviewing, interrogation, and criminal investigation claim that there are numerous accurate indicators of deception which can be readily used in field settings. The comparison of these claims with the research in psychology indicates that a great deal of the information found in criminal justice textbooks is erroneous. Further review indicates that in controlled studies criminal justice practitioners rarely detect deception at levels greater than chance or comparison groups of non‐practitioners. It is exceedingly difficult to detect deception in field settings without the help of technology or complicated instruments or aids.

Much of the information in criminal justice textbooks on detecting deception is erroneous and may have negatively affected practitioners to the extent that they are unable to detect deception effectively. Textbooks on interviewing, interrogation, and criminal investigation should be circumspect regarding an individual's ability to detect deception in field settings. Texts should refrain from presenting deception detection as a simple and accurate science. Practitioners should be cautious when attempting to detect deception in field settings.

The criminal justice and psychological literatures on detecting deception have not been synthesized before. This information will be useful to criminal justice practitioners who seek to detect deception.

The purpose of this study is to explore the views of practicing negotiators on their experiences of deception and their strategies for detecting deceptive behavior. A thematic analysis of interview data complements the existing experimental literature on deception and negotiation. The authors compare the experiences of practicing negotiators with the results found in experimental studies and provide practical recommendations for negotiators and managers regarding the detection of deception.

Data was collected from 19 practicing commercial negotiators in France by way of semi-structured interviews. The transcribed data was analyzed by way of thematic analysis using the software NVivo 12. Experiences and behaviors identified in the negotiation literature as key factors for the detection of deception acted as a coding framework.

A thematic analysis of the data revealed four themes related to the experience of deception that negotiators perceived as particularly important: the frequency, form, interpretation and consequences of deception. Further, the analysis revealed four factors that negotiators believed influenced their ability to detect deceptive communication: physical cues, such as body language and micro-expressions, and verbal cues, including contradictions and inconsistencies, emotional cues and environmental cues. Finally, the strategies described by negotiators to detect deception could be classified according to six themes: careful listening, asking questions, emotional intelligence, intuition, checking consistency and requesting evidence.

This study elicited the views of commercial negotiators without collecting information from their negotiation counterparts. Hence, it was not possible to verify whether the reported detection of deceptive communication was accurate. Because of optimism bias, the participants in the sample were likely to overrate their ability to detect deception. In part, this was helpful because the negotiators spoke freely about their strategies for dealing with deceptive counterparts allowing the identification of techniques to improve the efficacy of detecting deceptive communication.

Participants overwhelmingly expressed that there is a lack of training on deception in negotiation. It is suggested that the results of this study inform the development of training courses on the detection of deception. In particular, it is recommended that training courses should cover the following topics: how to anticipate and avoid deceptive behavior; how to effectively respond to deceptive behavior; the role of emotional intelligence in detecting deceptive behavior; careful listening and asking questions; and the role of intuition in detecting deception.

Prior empirical studies on the detection of deception have not specifically investigated the range of self-reported strategies used by practicing negotiators to detect deceptive communication. This study addresses this gap. This study complements existing experimental works by widening the spectrum of potential variables that play a role in the effective detection of deceptive communication.

The purpose of this paper is to investigate the effect of response bias and target gender on detecting deception.

Participants were randomly assigned to one of three experimental conditions: a stereotype condition (bogus training group), a tell-signs condition (empirically tested cues), and a control condition. Participants were required to decide whether eight targets were lying or telling the truth, based upon the information they had been given. Accuracy was measured via a correct or incorrect response to the stimuli. The data were then analyzed using a 2×2×3 mixed analysis of variance (ANOVA) to determine whether any main or interactional effects were present.

Results revealed training condition had no significant effect on accuracy, nor was there a within-subject effect of gender. However, there was a significant main effect of accuracy in detecting truth or lies, and a significant interaction between target gender and detecting truth or lies.

Future research should seek a larger sample of participants with a more extensive training aspect developed into the study, as the brief training offered here may not be fully reflective of the extent and intensity of training which could be offered to professionals.

Within the criminal justice system, the need for increased accuracy in detecting deception is of critical importance; not only to detect whether a guilty individual is being deceitful, but also whether someone is making a false confession, both to improve community safety by detaining the correct perpetrator for the crime but also to maintain public trust in the justice system. The present research provides a fresh insight into the importance of training effects in detecting deception.

To function effectively, police must separate lies from truth. Police, ideally, would be experts at this task, yet there is debate surrounding whether expertise in detecting deception is possible. Drawing upon literature outside of deception detection, the purpose of this paper is to explore whether subjects making deception judgments can improve their performance.

The sample was 19 students from two graduate-level classes. Subjects viewed six sets of videos over eight weeks. The first five sets displayed individuals reporting whether they cheated on an exam. The sixth set displayed individuals reporting whether they had committed a (mock) robbery. After each video, subjects judged whether the videoed individual was truthful, and then the actual status was revealed.

Subjects’ accuracy improved consistently over the first five sets of videos; from about 69 percent accuracy to about 89 percent accuracy. However, the accuracy for the sixth set of videos dropped dramatically to 46 percent. The results indicate that expertise in deception detection may be possible, but is likely to be limited in terms of generalizability.

The actual environment of police investigations is more variable than the study’s setting. Future studies should integrate inaccurate and incomplete feedback, which are realistic characteristics of investigations.

The findings suggest that, like other areas of expertise, it may be possible to develop expertise in detecting deception through the use of deliberate practice with accurate feedback.

This study combines three literature-substantiated criteria for developing deception detection expertise. The study environment involved regularity. Subjects were deliberately practicing, and subjects received accurate feedback.

This paper aims to describe requirements for a model that can assist in identity deception detection (IDD) on social media platforms (SMPs). The model that was discovered demonstrates the usefulness of the requirements. The aim of the model is to identify humans lying about their identity on SMPs.

The requirements of a model for IDD will be determined through a literature study combined with a study that identifies currently available identity related metadata on SMPs. This metadata refers to the attributes that describe a user account on an SMP. The aim is to restrict IDD to be only based on these types of attributes, as opposed to or combined with the contents of a single or multiple communications.

Data science experiments were conducted and in particular supervised machine learning models were discovered that indeed detects identity deception on SMPs with an area under the receiver operator characteristics curve (ROC-AUC) of 75.5 per cent.

SMPs allow any user to easily communicate with their friends or the general public at large. People can now be targeted at great scale, most often for malicious purposes. The reality is that many of these cyber-attacks involve some form of identity deception, where the attackers lie about who they are. Much focus to date has been on the identification of non-human deceptive accounts. This paper focuses on deceptive human accounts that target vulnerable individuals on SMPs.

This paper aims to examine the dynamics of emotional cues and cognitive cues in review fakeness. Additionally, the boundary condition (i.e. review valence) for the dynamics between emotional cues and cognitive cues is investigated.

This research conducted two studies, which analyzed restaurant and hotel reviews collected from Yelp.com. The authors adopted linguistic inquiry and word count 2015 to code review contents and tested the hypotheses using logistic regression.

Fake reviews contain more emotional cues compared with authentic reviews. Moreover, the dynamics of emotional cues and cognitive cues are salient among negative reviews.

This research provides implications to identify fake online reviews based on linguistic cues.

This research contributes to the literature by revealing the competition of mental resources between emotional and cognitive systems when deception is for harming others. Grounded in interpersonal deception theory, this paper investigates the interactive effect and complements the literature, which mainly used emotional cues and cognitive cues individually to detect fake reviews.

The purpose of this paper is to address the complexity of missing persons cases and highlight the linguistic differences that arise in this type of crime. Missing persons cases are typically very complex investigations. Without a body, crime scene forensics is not possible, and police are often left only with witness and suspect statements. Forensic linguistics methods may help investigators to prioritise or remove suspects. There are many competing approaches in forensic linguistic analysis; however, there is limited empirical research available on emerging methods.

This research investigates Statement Analysis, a recent development in linguistic analysis that has practical applications in criminal investigations. Real-world statements of individuals convicted of or found to be not guilty of their involvement in missing persons cases were used in the analyses. In addition, Behaviour Sequence Analysis was used to map the progressions of language in the suspects' statements.

Results indicated differences between the guilty and innocent individuals based on their language choices, for example, guilty suspects in missing [alive] cases were found more likely to use passive language and vague words because of high levels of cognitive load associated with the several types of guilty knowledge suspects in missing persons cases possess. Of particular interest is the use of untruthful words in the innocent suspects’ statements in missing [murdered] cases. While typically seen in deceptive statements, untruthful words in innocent statements may result because of false acquittals.

This research provides some support for Statement Analysis as a suitable approach to analysing linguistic statements in missing persons cases.

With the outset of automatic detection of information, misinformation, and disinformation, the purpose of this paper is to examine and discuss various conceptions of information, misinformation, and disinformation within philosophy of information.

The examinations are conducted within a Gricean framework in order to account for the communicative aspects of information, misinformation, and disinformation as well as the detection enterprise.

While there often is an exclusive focus on truth and falsity as that which distinguish information from misinformation and disinformation, this paper finds that the distinguishing features are actually intention/intentionality and non-misleadingness/misleadingness – with non-misleadingness/misleadingness as the primary feature. Further, the paper rehearses the argument in favor of a true variety of disinformation and extends this argument to include true misinformation.

The findings are novel and pose a challenge to the possibility of automatic detection of misinformation and disinformation. Especially the notions of true disinformation and true misinformation, as varieties of disinformation and misinformation, which force the true/false dichotomy for information vs mis-/disinformation to collapse.

Asynchronous Video Interviews (AVIs) incorporating Artificial Intelligence (AI)-assisted assessment has become popular as a pre-employment screening method. The extent to which applicants engage in deceptive impression management (IM) behaviors during these interviews remains uncertain. Furthermore, the accuracy of human detection in identifying such deceptive IM behaviors is limited. This study seeks to explore differences in deceptive IM behaviors by applicants across video interview modes (AVIs vs Synchronous Video Interviews (SVIs)) and the use of AI-assisted assessment (AI vs non-AI). The study also investigates if video interview modes affect human interviewers' ability to detect deceptive IM behaviors.

The authors conducted a field study with four conditions based on two critical factors: the synchrony of video interviews (AVI vs SVI) and the presence of AI-assisted assessment (AI vs Non-AI): Non-AI-assisted AVIs, AI-assisted AVIs, Non-AI-assisted SVIs and AI-assisted SVIs. The study involved 144 pairs of interviewees and interviewers/assessors. To assess applicants' deceptive IM behaviors, the authors employed a combination of interviewee self-reports and interviewer perceptions.

The results indicate that AVIs elicited fewer instances of deceptive IM behaviors across all dimensions when compared to SVIs. Furthermore, using AI-assisted assessment in both video interview modes resulted in less extensive image creation than non-AI settings. However, the study revealed that human interviewers had difficulties detecting deceptive IM behaviors regardless of the mode used, except for extensive faking in AVIs.

The study is the first to address the call for research on the impact of video interview modes and AI on interviewee faking and interviewer accuracy. This research enhances the authors’ understanding of the practical implications associated with the use of different video interview modes and AI algorithms in the pre-employment screening process. The study contributes to the existing literature by refining the theoretical model of faking likelihood in employment interviews according to media richness theory and the model of volitional rating behavior based on expectancy theory in the context of AVIs and AI-assisted assessment.

Drawing on the theoretical domain of speech act theory (SAT) and a discussion of its suitability for setting the agenda for social media research, this study aims to explore a range of research directions that are both relevant and conceptually robust, to stimulate the advancement of knowledge and understanding of online verbatim data.

Examining previously published cross-disciplinary research, the study identifies how recent conceptual and empirical advances in SAT may further guide the development of text analytics in a social media context.

Decoding content and function word use in customers’ social media communication can enhance the efficiency of determining potential impacts of customer reviews, sentiment strength, the quality of contributions in social media, customers’ socialization perceptions in online communities and deceptive messages.

Considering the variety of managerial demand, increasing and diverging social media formats, expanding archives, rapid development of software tools and fast-paced market changes, this study provides an urgently needed, theory-driven, coherent research agenda to guide the conceptual development of text analytics in a social media context.