Online Deception Detection Refueled by Real World Data Collection [PDF]
arXiv, 2017 The lack of large realistic datasets presents a bottleneck in online deception detection studies. In this paper, we apply a data collection method based on social network analysis to quickly identify high-quality deceptive and truthful online reviews from Amazon.
Wenlin Yao +3 more
arxiv +3 more sources
Emotional intelligence and mismatching expressive and verbal messages: a contribution to detection of deception. [PDF]
PLoS ONE, 2014 Processing facial emotion, especially mismatches between facial and verbal messages, is believed to be important in the detection of deception. For example, emotional leakage may accompany lying. Individuals with superior emotion perception abilities may
Jerzy Wojciechowski +2 more
doaj +3 more sources
Self and other-perceived deception detection abilities are highly correlated but unassociated with objective detection ability: Examining the detection consensus effect [PDF]
Scientific ReportsSubjective lying rates are often strongly and positively correlated. Called the deception consensus effect, people who lie often tend to believe others lie often, too.
David M. Markowitz
doaj +2 more sources
Proceedings of the AAAI Conference on Artificial Intelligence, 2017 We present a system for covert automated deception detection using information available in a video. We study the importance of different modalities like vision, audio and text for this task. On the vision side, our system uses classifiers trained on low level video features which predict human micro-expressions.
Zhe Wu +3 more
openalex +4 more sources
Improved semi-supervised autoencoder for deception detection. [PDF]
PLoS ONE, 2019 Existing algorithms of speech-based deception detection are severely restricted by the lack of sufficient number of labelled data. However, a large amount of easily available unlabelled data has not been utilized in reality.
Hongliang Fu +4 more
doaj +2 more sources
How humans impair automated deception detection performance
Acta Psychologica, 2021 Background: Deception detection is a prevalent problem for security practitioners. With a need for more large-scale approaches, automated methods using machine learning have gained traction. However, detection performance still implies considerable error
Bennett Kleinberg, Bruno Verschuere
doaj +2 more sources
The Limits of Conscious Deception Detection: When Reliance on False Deception Cues Contributes to Inaccurate Judgments [PDF]
Frontiers in Psychology, 2020 People are generally too trusting, which decreases their ability to detect deceit. This suggests that distrust could enhance our deception detection abilities. Yet, a state of distrust may induce deliberative conscious thought.
Mariëlle Stel +3 more
doaj +2 more sources
Deception Detection in Politics: Can Voters Tell When Politicians are Lying? [PDF]
Polit Behav, 2023 Mattes K, Popova V, Evans JR.
europepmc +3 more sources
The effect of statement type and repetition on deception detection. [PDF]
Cogn Res Princ Implic, 2019 Cash DK, Dianiska RE, Lane SM.
europepmc +2 more sources
Five Reasons Why I Am Skeptical That Indirect or Unconscious Lie Detection Is Superior to Direct Deception Detection. [PDF]
Front Psychol, 2019 Levine TR.
europepmc +3 more sources