When lovers become leery: The relationship between suspicion and accuracy in detecting deception

McCornack, Steven A.; Levine, Timothy R.

doi:10.1080/03637759009376197

Cited by 118 publications

(104 citation statements)

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“…Farquhar, 2005). Research shows that people are more truth-biased when interacting face-to-face (Buller et al, 1991), when they know the person they are talking to (McCornack & Parks, 1986), and they are not forewarned of impending deception (e.g., Levine et al, 2000;McCornack & Levine, 1990). Each of these conditions is often met in everyday situations, but is seldom the case in deception detection experiments.…”

Section: Resultsmentioning

confidence: 99%

“…Theoretically, the effect of base-rate on accuracy would become stronger when communication is face-to-face, when interaction is with a close relational partner, and when people are not primed to be suspicious or prompted to expect deception (Buller et al, 1991;McCornack & Levine, 1990;McCornack & Parks, 1986). Alternatively, previous research would suggest weaker results when judges receive detection training, when they have occupational experience in lie detection, or when they are incarcerated as these conditions lower truth-bias, but do not substantially increase overall accuracy (Bond, Malloy, Arias, Nunn, & Thompson, 2005;Frank & Feeley, 2003;Levine, Feeley, McCornack, Harms, & Hughes, 2005;Meissner & Kassin, 2002).…”

Section: Resultsmentioning

confidence: 99%

“…Explanations for truth-bias include the cognitive processes involved in mentally representing true and false information (Gilbert, 1991) and fundamental principles in how language is understood (Grice, 1989;McCornack, 1992). Truth-bias is especially pronounced when people interact face-to-face (Buller, Strzyzewski, & Hunsaker, 1991), when people know the message source (McCornack & Parks, 1986), and in studies where the participants are unaware that their task is to detect lies (e.g., Levine et al, 2000;McCornack & Levine, 1990). Levine et al (1999) observed that the research documenting the accuracy-is-slightlyabove-50% conclusion typically share two important features.…”

Section: Deception Detection Accuracymentioning

confidence: 99%

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Deception Detection Accuracy is a Predictable Linear Function of Message Veracity Base-Rate: A Formal Test of Park and Levine's Probability Model

Levine

Kim

Park

et al. 2006

Communication Monographs

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This study provided the first empirical test of point predictions made by the Park-Levine probability model of deception detection accuracy. Participants viewed a series of interviews containing truthful answers, unsanctioned, high-stakes lies, or some combination of both. One randomly selected set of participants (n0/50) made judgments where the probability that each message was honest was P(H)0/.50. Accuracy judgments in this condition were used to generate point predictions generated from the model and tested against the results from a second set of data (n 0/413). Participants were randomly assigned to one of eight base-rate conditions where the probability that a message was honest systematically varied from 0.00 to 1.00. Consistent with the veracity effect, participants in P(H)0/.50 condition were significantly more likely to judge messages as truths than as lies, and consequently truths (67%) were identified with greater accuracy than lies (34%). As predicted by the model, overall accuracy was a linear function of message veracity base-rate, the base-rate induction explained 24% of the variance in accuracy scores, and, on average, raw accuracy scores for specific conditions were predicted to within approximately9/2.6%. The findings show that specific deception detection accuracy scores can be precisely predicted with the Park-Levine model.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Deception Detection Accuracymentioning

confidence: 99%

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Deception Detection Accuracy is a Predictable Linear Function of Message Veracity Base-Rate: A Formal Test of Park and Levine's Probability Model

Levine

Kim

Park

et al. 2006

Communication Monographs

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“…People are more likely to make lie judgments when made suspicious than when they are not suspicious (e.g., Levine & McCornack, 1991; McCornack & Levine, 1990;Stiff et al, 1992;Toris & DePaulo, 1985), even when cognitive resources are limited by means of a cognitive load (M. G. Millar & Millar, 1997 …”

Section: Truth Bias As a Cognitive Defaultmentioning

confidence: 99%

“…In fact, in contrast to default theories, in certain contexts it may take more effort to believe what others say is true. People are more likely to make lie judgments when made suspicious than when they are not suspicious (e.g., Levine & McCornack, 1991;McCornack & Levine, 1990;Stiff et al, 1992;Toris & DePaulo, 1985), even when …”

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confidence: 99%

ALIED: Humans as adaptive lie detectors.

Street¹

2015

Journal of Applied Research in Memory and Cognition

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People make for poor lie detectors. They have accuracy rates comparable to a coin toss, and come with a set of systematic biases that sway the judgment. This pessimistic view stands in contrast to research showing that people make informed decisions that adapt to the context they operate in. The current article proposes a new theoretical direction for lie detection research. I argue that lie detectors make informed, adaptive judgments in a low-diagnostic world. This Adaptive Lie Detector People have little idea of when they are being lied to, with accuracy rates only marginally above chance (Bond & DePaulo, 2006;Kraut, 1980). They seem to have the wrong beliefs about what cues give away liars (The Global Deception Research Team, 2006), and even with training there is only a modest increase in accuracy (Frank & Feeley, 2003;Hauch, Sporer, Michael & Meissner, 2014). What is more, there is a robust bias to take what others say at face value and believe it is the truth, dubbed the 'truth bias' (Bond & DePaulo, 2006;McCornack & Parks, 1986), which some have taken as evidence that people are gullible (Buller & Burgoon, 1996;O'Sullivan, 2003) and not in control of this bias (Gilbert, 1991). This pessimistic view has been dominant in the field for some time (e.g., Bond & DePaulo, 2006;Kraut, 1980;Mandelbaum, 2014;Vrij, Granhag & Porter, 2010). The current article takes a new position. I draw on recent advances and present a more optimistic view of the lie detector: as one who makes informed judgments in a low diagnostic world. In particular, I take a more Brunswikian point of view and argue that people adapt their judgment strategies based on the nature of the information available (see Brunswik, 1952). This is referred to as the Adaptive Lie Detector account (ALIED). Overview of the AccountThe ALIED account is inspired by advances in the decision-making literature, in particular the adaptive decision making perspective (Gigerenzer & Selten, 2001; Gigerenzer, Todd & The ABC Group, 1999;Platzer & Bröder, 2012;Simon, 1990).In an information-limited world and with a finite cognitive capacity, people can arrive at satisfactorily accurate judgments. By adapting to the context, one can put those limited resources to best use. Simplified strategies such as recognition and heuristics allow for 'satisficing' inferences to be made (Gigerenzer & Selten, 2001;Simon, 1956Simon, , 1990. Notably, people do not default to leaning on their contextual knowledge, 4 but vicariously adapt what information they use in order to make an informed judgment (Brunswik, 1952). These simplified context-general rules help form decisions under uncertainty (Gigerenzer & Gaissmaier, 2011;Simon, 1990).ALIED proposes that people attempt to form a judgment about a specific statement by using information that pertains directly to that specific statement. For instance, a confession that the statement is false is an individuating piece of information that can help us decide whether this particular statement is true or false.Similarly, verbal cues...

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Deception with Technology

Hancock

Guillory

2015

The Handbook of the Psychology of Communication Technology

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When lovers become leery: The relationship between suspicion and accuracy in detecting deception

Cited by 118 publications

References 11 publications

Deception Detection Accuracy is a Predictable Linear Function of Message Veracity Base-Rate: A Formal Test of Park and Levine's Probability Model

Deception Detection Accuracy is a Predictable Linear Function of Message Veracity Base-Rate: A Formal Test of Park and Levine's Probability Model

ALIED: Humans as adaptive lie detectors.

Deception with Technology

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