Human Deception Detection

34
ORIGINAL ARTICLE Cognitive Biases and Nonverbal Cue Availability in Detecting Deception Judee K. Burgoon 1 , J. Pete Blair 2 , & Renee E. Strom 3 1 Center for the Management of Information, University of Arizona, Tucson, AZ 85719 2 Department of Criminal Justice, Texas State University, San Marcos, TX 78666 3 Department of Communication Studies, St. Cloud State University, St. Cloud, MN 56301 In potentially deceptive situations, people rely on mental shortcuts to help process informa- tion. These heuristic judgments are often biased and result in inaccurate assessments of sender veracity. Four such biases—truth bias, visual bias, demeanor bias, and expectancy violation bias—were examined in a judgment experiment that varied nonverbal cue avail- ability and deception. Observers saw a complete videotaped interview (full access to visual, vocal, and verbal cues), heard the complete interview (vocal and verbal access), or read a transcript (verbal access) of a truthful or deceptive suspect being questioned about a mock theft and then rated the interviewee on information, behavior, and image management and truthfulness. Results supported the presence of all four biases, which were most evident when interviewees were deceptive and observers had access to all visual, vocal, and verbal modalities. Deceivers’ messages were judged as increasingly complete, honest, clear, and rel- evant; their behavior as more involved and dominant; and their overall demeanor as more credible, with the addition of nonverbal cues. Deceivers were actually judged as more credi- ble than truthtellers in the audiovisual modality, whereas best discrimination and detection accuracy occurred in the audio condition. Results have implications for what factors influ- ence judgments of a sender’s credibility and accuracy in distinguishing truth from decep- tion, especially under conditions where senders are producing messages interactively. doi:10.1111/j.1468-2958.2008.00333.x Cognitive biases, nonverbal cue availability, and deception detection One of the most well-documented claims in the deception literature is that humans are poor detectors of deception. A recent meta-analysis reveals that although people show a statistically reliable ability to discriminate truths from lies, overall accuracy rates average 54% or only a little above chance (Bond & DePaulo, 2006). A primary causal mechanism cited for biased judgments of deception and credibility is reliance on heuristic social information processing—a nonanalytic orientation to Corresponding author: Judee K. Burgoon; e-mail: [email protected] This article was accepted under the editorship of Jim Dillard. Human Communication Research ISSN 0360-3989 572 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association HUMAN COMMUNICATION research

Transcript of Human Deception Detection

Page 1: Human Deception Detection

ORIGINAL ARTICLE

Cognitive Biases and Nonverbal CueAvailability in Detecting Deception

Judee K. Burgoon1, J. Pete Blair2, & Renee E. Strom3

1 Center for the Management of Information, University of Arizona, Tucson, AZ 85719

2 Department of Criminal Justice, Texas State University, San Marcos, TX 78666

3 Department of Communication Studies, St. Cloud State University, St. Cloud, MN 56301

In potentially deceptive situations, people rely on mental shortcuts to help process informa-

tion. These heuristic judgments are often biased and result in inaccurate assessments of

sender veracity. Four such biases—truth bias, visual bias, demeanor bias, and expectancy

violation bias—were examined in a judgment experiment that varied nonverbal cue avail-

ability and deception. Observers saw a complete videotaped interview (full access to visual,

vocal, and verbal cues), heard the complete interview (vocal and verbal access), or read

a transcript (verbal access) of a truthful or deceptive suspect being questioned about a mock

theft and then rated the interviewee on information, behavior, and image management

and truthfulness. Results supported the presence of all four biases, which were most evident

when interviewees were deceptive and observers had access to all visual, vocal, and verbal

modalities. Deceivers’ messages were judged as increasingly complete, honest, clear, and rel-

evant; their behavior as more involved and dominant; and their overall demeanor as more

credible, with the addition of nonverbal cues. Deceivers were actually judged as more credi-

ble than truthtellers in the audiovisual modality, whereas best discrimination and detection

accuracy occurred in the audio condition. Results have implications for what factors influ-

ence judgments of a sender’s credibility and accuracy in distinguishing truth from decep-

tion, especially under conditions where senders are producing messages interactively.

doi:10.1111/j.1468-2958.2008.00333.x

Cognitive biases, nonverbal cue availability, and deception detection

One of the most well-documented claims in the deception literature is that humans

are poor detectors of deception. A recent meta-analysis reveals that although peopleshow a statistically reliable ability to discriminate truths from lies, overall

accuracy rates average 54% or only a little above chance (Bond & DePaulo, 2006).A primary causal mechanism cited for biased judgments of deception and credibilityis reliance on heuristic social information processing—a nonanalytic orientation to

Corresponding author: Judee K. Burgoon; e-mail: [email protected] article was accepted under the editorship of Jim Dillard.

Human Communication Research ISSN 0360-3989

572 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

HUMANCOMMUNICATION research

Page 2: Human Deception Detection

information processing in which only some informational cues are carefully consid-ered (Chaiken, 1980; Todorov, Chaiken, & Henderson, 2002). As mental shortcuts,

people invoke cognitive heuristics, simple decision rules that arise from conventionalbeliefs and expectations and that are used repeatedly in daily interactions (Tversky &

Kahneman, 1974). These mental shortcuts may yield biased information processingand faulty judgments of others’ veracity (Fiedler, 1993).

Four especially salient and potentially interrelated biases are truth bias (the

tendency to overestimate others’ truthfulness), visual bias (the tendency to placemore reliance on visual than vocal, linguistic, and other forms of social information),

demeanor bias (the tendency to judge some senders’ communication styles as cred-ible irrespective of their actual truthfulness), and expectancy violations bias (the

tendency to judge unusual behavior as deceptive). Together, these biases mayaccount not only for poor detection of deception but also more generally for judg-

ments of communicator credibility.The interrelationships among these biases have not been investigated previously.

It may be that some are subordinate to, or artifacts of, others. The visual bias, for

example, may be the product of demeanor and expectancy violations biases or it maybe a product of other factors such as the information richness of the medium. Thus,

a central objective of the investigation to be reported was to examine the interrela-tionships among these biases and their ultimate impact on veracity judgments.

A second objective was to test these biases when judgments are applied to thekinds of message exchange that typify normal, ongoing interaction. The Bond and

DePaulo (2006) meta-analysis, though quite comprehensive, included very few stud-ies in which the stimuli that were judged when produced under fully interactive

conditions, that is, ones in which senders engaged in ongoing and interdependentsocial interaction with the intended targets of their deceit.1 Given that deceptiontypically is embedded in ongoing interaction rather than judged in isolation, and

given that judgments made of naturalistic interaction differ from those made of brief,experimentally controlled stimuli (Motley & Camden, 1988), knowledge of how

people make veracity judgments should be founded on the kinds of stimuli theynormally encounter rather than on brief, decontextualized snippets.

That the bulk of experimental stimuli have been less than 60 seconds in length(see Bond & DePaulo, 2006; DePaulo et al., 2003) renders most of the extant liter-

ature mute as to what happens beyond the first minute of interaction. It may be thatas a deceptive episode unfolds, deception becomes more difficult to detect becausedeceivers capitalize on the features of interpersonal interaction to regulate their

performances more effectively and thus evade detection (Burgoon & Buller, 2004).Conversely, messages intended to deceive interlocutors might be more transparent in

their intent and therefore more readily detected as observers gain extended exposureto the subtleties of deceptions enmeshed in the ongoing conversational context and

they consider simultaneous or serial incongruities in different information streams,such as when a pleasant face accompanies a strained voice. The Bond and DePaulo

(2006) meta-analysis results suggest such an explanation.

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 573

Page 3: Human Deception Detection

The issue of what biases influence judgments of a person’s veracity under con-ditions of interactive message production was examined in a factorial experiment in

which the stimuli to be judged were interviewees who had been questioned abouta mock theft. Observers judged a truthful or deceptive interview under one of the

three modalities: text, audio, or audiovisual (AV). The modality manipulation testedhow the addition or deletion of visual and vocal nonverbal demeanor cues affectedjudgments. Observers in the text condition had access only to a transcript of an

interview and so had no access to nonverbal demeanor cues. Observers in the audiocondition heard a recorded interview and so had access to both words and voice,

thus exposing them to vocalic demeanor cues and to possible channel discrepancies.Those in the AV condition watched a videotaped interview and so, in addition to

words and voice, had access to visual nonverbal cues as well as to any discrepanciesamong the three channels. Observers judged interviewee communication and

decided if the interviewee was innocent or guilty.Other design features were also introduced to maximize the ecological validity of

the results. The mock theft task, coupled with monetary incentives for success, was

expected to heighten interviewees’ motivation and arousal and hence produce sam-ples of behavior more akin to what transpires in higher stakes, real-world deception

than is commonly achieved in laboratory deception experiments. Moreover, decep-tive interviewees were not constrained to produce outright lies; they could employ

whatever strategies they chose to enact, including ambiguity, concealment, equivo-cation, and other forms of obfuscation.

Though not the primary thrust, this investigation also has relevance to newmedia in that it speaks to how judgments of communicator veracity vary according

to the medium in which receivers access another’s messages. To the extent that somemedia foster or inhibit biased information processing more than others, users mayselect media according to how well they suit their impression management aims.

This holds as much for senders who may use media for ulterior motives as forreceivers who are seeking to form the most accurate judgments of others.

Literature review and hypotheses

Everyday truth judgments must often rely on stereotypical knowledge that is

detached from the assessment of authentic cues (Fiedler, 1993). Though cognitiveheuristics often lead to efficient and correct decisions, they can just as easily lead tobiased judgments. The latter case is of interest here. Pared-down processing is espe-

cially common when receivers are unmotivated or have limited cognitive resourcesto appraise carefully a sender’s communicative behavior and so become ‘‘cognitive

misers,’’ expending the least possible amount of cognitive effort necessary to arrive ata judgment (Fiske, 1993; Fiske & Taylor, 1991). Processing deceptive messages

should be less taxing for observers than for participants, inasmuch as observersare freed from the complex multitasking that occupies conversational participants

(Buller & Burgoon, 1996). Nonetheless, the tendency to eschew full analytical energy

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

574 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 4: Human Deception Detection

should still be present among observers, for whom the consequences of makingerroneous judgments are small. The current experiment centered on the kinds of

biases that might operate in routine, day-to-day judgments of another’s veracity, inother words, when cognitive miserliness might be most probable.

Truth bias

Of the four biases investigated here, the truth bias is the most cited and docu-

mented one in the deception literature (e.g., Kraut & Higgins, 1984; Levine, Park, &McCornack, 1999; McCornack & Parks, 1986; O’Sullivan, Ekman, & Friesen, 1988;

Zuckerman, DeFrank, Hall, Larrance, & Rosenthal, 1979; Zuckerman, DePaulo, &Rosenthal, 1981). There are at least two different conceptualizations of truth bias.

One is as an a priori belief, expectation, or presumption that reflects theoft-observed tendency to assume communicators are truthful most of the time

(Clark & Clark, 1977; O’Sullivan, 2003). This presumption of truthfulness, whichmight be labeled a truthfulness heuristic, finds roots in Grice’s (1989) principle ofcooperative discourse. It also comports with what Gilbert and colleagues (Gilbert,

Krull, & Malone, 1990; Gilbert, Pelham, & Krull, 1988) described as a Spinozanview of human information processing in which all incoming information is ini-

tially tagged as truthful and only subsequently revised if something occasions theneed for appraisal and revision.

The other conceptualization follows common usage for the term ‘‘bias’’ in psy-chometric literature and statistics, where a bias represents a departure from the true

state of affairs (e.g., a biased sample statistic over- or underestimates the true meanvalue of a population) and therefore is inaccurate by definition. Put in deception

terms, a truth bias reflects a tendency to judge more messages as truths than lies,independent of their actual veracity (McCornack & Parks, 1986; Zuckerman,DePaulo et al., 1981). When judging another’s veracity, it results in an overestimate

of actual number of truths relative to the base rate of actual truthfulness; a lie biasreflects an underestimate of the same. Conceptualized in this manner, truth biases

may be a byproduct of, or closely aligned with, leniency and positivity biases.Presence of a truthfulness heuristic and/or truth bias has been amply docu-

mented in a variety of contexts (e.g., Anolli, Balconi, & Ciceri, 2003; Buller, Burgoon,White, & Ebesu, 1994; Buller, Strzyzewski, & Hunsaker, 1991; McCornack & Parks,

1986; Stiff, Kim, & Ramesh, 1992; Vrij & Mann, 2001). People rating messageveracity consistently exhibit a tendency to judge most messages as truthful, evenwhen the base rate of deception is varied (Levine, Kim, Park, & Hughes, 2006; Levine

et al., 1999). The first hypothesis sought to replicate this tendency to err in thedirection of truthfulness when judging message veracity but to extend it to interac-

tive message production with the aforementioned modifications to methods (uncon-strained, naturalistic, and motivated discourse production by senders; longer stimuli

to judge). These methodological features pose a more stringent test of truth bias inthat motivated, extended discourse could make deception more detectable or intro-

duce statistical error variance that would mitigate judgmental bias. The hypothesis

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 575

Page 5: Human Deception Detection

posited that ‘‘observers err in the direction of judging more messages as true than thebase rate of truthful and deceptive stimuli being judged’’ (Hypothesis 1).

Visual and demeanor biases

The visual bias is a tendency to assign primacy to visual information over otherforms of social information (DePaulo & Rosenthal, 1979; Noller, 1985; Stiff et al.,1989). Extensive research on channel reliance has shown systematic differences in

judgments of messages with text only, audio only, video only, and AV delivery(Burgoon, 1985, 1994; DePaulo, Rosenthal, Green, & Rosenkrantz, 1982; DePaulo,

Zuckerman, & Rosenthal, 1980). Observers attend more closely to facial than to bodyor voice cues (Bauchner, Kaplan, & Miller, 1980; Buller et al., 1991; Ekman & Friesen,

1974) despite the fact that facial cues typically are the least diagnostic in identify-ing deception (Feldman, 1976; Hocking, Bauchner, Kaminski, & Miller, 1979;

Zuckerman, Larrance, Spiegel, & Klorman, 1981).Stiff et al. (1989) advanced two explanations for the visual cue primacy effect: A

distraction hypothesis—that nonverbal visual cues distract from processing diagnos-

tic (reliable) verbal information—and a situational familiarity hypothesis—that reli-ance shifts primarily to verbal content (as compared to using both verbal and

nonverbal information) when the situation is familiar. Experimental results attestedto a visual primacy effect: Visual cues had a substantial impact on judgments of

truthfulness, vocal cues had a significant though weaker effect, and verbal variationsdid not alter judgments. A second experiment also showed that reliance on non-

verbal cues was greater in the unfamiliar than in the familiar circumstance. However,two design features of the Stiff et al. (1989) study introduce some equivocality to the

conclusions. Actors followed a tight script rather than producing the kinds of naturaldiscourse present in normal deceptive interviews. Also, of the six cues that weremanipulated, gaze aversion and audible pauses are stereotypical cues, whereas adap-

tors, postural shifts, speech errors, and silent pauses can be reliable (though by nomeans ever-present) indicators of deceit. Unclear, then, is if ratings of deceptiveness

reflected accurate detection or stereotypic judgments. The current experiment wasdesigned to untangle and clarify the effects of availability of nonverbal cues, includ-

ing vocal ones, about which Stiff et al. (1989) had no hypotheses. To replicate theordering found by Stiff et al., we predicted that ‘‘judgments of a person’s truthfulness

increase ordinally with nonverbal cue availability from text (verbal-only) to audio(verbal 1 vocal) to AV (verbal 1 vocal 1 visual) presentations’’ (Hypothesis 2).2

These predictions beg the question of exactly why the presence of visual infor-

mation is biasing. After all, visual primacy in itself does not guarantee biased judg-ments; bias should result only if observers attend to incorrect rather than correct

cues. We believe there are multiple, and not mutually exclusive, causal mechanismsat work, among them qualitative features of senders’ communication style. Inter-

personal deception theory (IDT; Buller & Burgoon, 1994, 1996; Burgoon & Buller,2004) holds that deceivers engage in three classes of strategic communication that

make detection of deceit difficult. Information management concerns the ways in

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

576 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 6: Human Deception Detection

which deceivers manipulate the verbal contents of their messages by alteringthe quantity, quality, clarity, and directness of message elements (Burgoon, Buller,

Guerrero, Afifi, & Feldman, 1996; McCornack, Levine, Morrison, & Lapinski, 1996).Relative to truthful messages, deceptive messages may be briefer with sparser details;

less clear and straightforward; and more indirect, depersonalized, and irrelevant.Behavior management concerns the control of specific nonverbal behaviors thataccompany verbal messages. Deceivers strive to create the appearance of con-

versational normalcy and involvement (Burgoon, Buller, Floyd, & Grandpre, 1996;Burgoon, Buller, White, Afifi, & Buslig, 1999; White & Burgoon, 2001). Image

management concerns more global efforts to present the self in a favorable lightand to reduce one’s apparent culpability should deceit be discovered (DePaulo,

1992).The components of strategic communication together can be viewed as synon-

ymous with demeanor bias, which is the tendency for some communicators toevoke general impressions of honesty and truthfulness irrespective of their actualveracity (Zuckerman, Larrance, et al., 1981).3 Access to visual nonverbal cues

should magnify demeanor bias by exposing observers to those controllable cuessuch as smiles, facial expressions, eye contact, gestures, spacing, and dress that are

deceivers’ stock in trade when attempting to ‘‘put their best face forward’’ (Bond,Kahler, & Paolicelli, 1985; Riggio, Tucker, & Throckmorton, 1987). Notwithstand-

ing variability in social skills, motivated deceivers should employ a variety ofstrategies to mount a credible performance, and their strategic advantage should

be realized most strongly when a richer array of social cues is available to observers.Although visual modalities conceivably could benefit receivers over senders by

affording them rich veins of social information to mine, the task of interpretingmultiple streams of information increases cognitive demands that ironically maymake receivers more prone to rely on heuristics precisely because there are so many

channels and cues to decode. Comparatively, biases may be less pronounced whenfewer nonverbal channels are available because differences in sender demeanor bias

are liable to be less marked and to have less chance of fostering familiarity and trustin message recipients or observers. We therefore hypothesized that ‘‘demeanor bias

varies with nonverbal cue availability such that (a) information management,(b) behavior management, and (c) image management increase ordinally from text

to audio to AV’’ (Hypothesis 3).Verifying these predictions presents a methodological conundrum because

a deceiver’s goal is to approximate the normal communication of truthtellers (Buller

& Burgoon, 1996; Burgoon, Buller, Floyd, et al., 1996). If successful, deceivers maymatch the levels of, say, involvement and perceived trustworthiness of truthtellers,

making any demeanor differences due to deception imperceptible. If, however,modality alters attention to visual cues, then modality may interact with deception

to affect what observers perceive. We therefore posed as a research question: ‘‘Dotruth and deception interact to influence information management, behavior man-

agement, and image management’’ (RQ1)?

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 577

Page 7: Human Deception Detection

Expectancy violations bias

Although the demeanor bias focuses on credibility-inducing behavior, the fourth

bias focuses on suspicion-provoking behavior. Expectancy violations bias is thetendency to infer deception from abnormal, ‘‘fishy-looking’’ behavior (Bond et al.,

1992). Expectancy violations theory (Burgoon, 1983; Burgoon & Burgoon, 2001)postulates that deviations from normative behaviors are arousing and divert atten-tion to the unexpected act. IDT and many other theories of deception (Afifi &

Weiner, 2004; Johnson, Grazioli, Jamal, & Berryman, 2001; Swets, 2000) assert thatdeceptive behavior is often unexpected, anomalous, or deviant. Tests of IDT have

shown that deceptive performances often suffer some initial impairment butimprove over time as deceivers strategically repair their communication (Buller

& Burgoon, 1994; Burgoon, Buller, White, et al., 1999; Burgoon, Buller, & Floyd,2001), which should mitigate expectancy violations. Thus, evidence of an expec-

tancy violations bias would imply that despite senders’ efforts to manage theirperformance, they still inadvertently give off signs of deceit that are detected by

receivers.Any such signs should appear differentially according to which nonverbal and

verbal channels are available to observers. Access to visual, vocal, and verbal cues

could create more expectancy violations because three different channels of infor-mation—visual, auditory, and verbal—are more difficult for senders to coordinate

and may expose observers to more suspicion-arousing channel discrepancies. Vocalcues can be very reliable indicators of deceit (DePaulo et al., 2003) possibly because

they deviate from customary vocal patterns and escape deceivers’ self-monitoring.Text de facto lacks channel discrepancies, but odd verbal behavior might become

more glaring without the distractions of nonverbal cues. These alternatives led us topose as a research question: ‘‘Does modality interact with deception to producejudgments of negative expectancy violations’’ (R2)?

Detection accuracy under different modalities

Although detection accuracy reports often combine truth and deception detectionwithin the same estimates, it is important to distinguish deception detection accu-

racy from truth detection accuracy, which may differ markedly (Burgoon, Buller,Ebesu, & Rockwell, 1994; Levine et al., 1999; Vrij & Mann, 2001). False alarms

(judging truths as deception) and false negatives (judging deception as truths) canalso be calculated (Green & Swets, 1966). As regards deception detection accuracy, the

picture that emerges so far is of individuals entering communicative situations withstrong proclivities to view others as truthful, to be drawn to visual information moreso than other nonverbal social cues, and, when accessing visual cues, to fall victim to

senders’ strategic efforts to manage their messages and overall demeanor. The onlybias working to benefit receivers is expectancy violations due to channel discrep-

ancies or to the sheer number of cues that could be at odds with normative socialpatterns. The net result of these various biases should be to yield very poor detection

accuracy under the visual modality.

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

578 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 8: Human Deception Detection

Text, too, should produce poor detection accuracy, but two countervailingforces—the diagnosticity of verbal cues and detachment between sender and

receiver—should net it higher accuracy than modalities with nonverbal cues. First,verbal cues are not inherently inscrutable. Deception ought to be, and is, detectable

from textual features (Vrij, 2000; Zhou, Burgoon, Twitchell, & Nunamaker, 2004).That said, accuracy may be attenuated somewhat by the fact that untrained detectorslack familiarity with linguistic clues to deception and tend to favor stereotypical cues

over valid ones (Buller et al., 1994; Zuckerman & Driver, 1985). Second, text fails toelicit the same sense of connection and involvement with message senders that

happens when nonverbal cues are present (e.g., Burgoon et al., 1999–2000; Burgoon,Stoner, Bonito, & Dunbar, 2003; Ramirez & Burgoon, 2004). This detachment may

introduce greater objectivity but also may dampen overall attentiveness to socialinformation, again causing text-based judgments to suffer some inaccuracy but to

a lesser extent than AV-based judgments.In the middle are judgments based on the combination of vocal and verbal cues.

The voice is a rich source of social information. Its ability to promote involvement

and intimacy often evokes positive responses that could be truth biasing. For exam-ple, Atoum and Al-Simadi (2000) found that speakers were judged as more honest

and attractive when the speaker could be heard (i.e., in an AV or audio modality)than when just seen (in a video-only modality). Yet, the voice also lacks many of the

known stereotypical (and incorrect) cues that people rely upon to make veracityjudgments. The absence of stereotypical cues may encourage judges to attend to

more reliable indicators of veracity such as pitch, hesitancies, and response latencies.Hence, audio-based judgments may attain greater detection accuracy.

The Bond and DePaulo (2006) meta-analysis supports these conclusions, report-ing lowest deception detection accuracy in a visual-only mode, better accuracy withverbal transcriptions, and best with audio or AV modalities. (Among visual cues,

detectability is worse from the face only or body only than the combination of thetwo.) Thus, access to visual cues, especially facial ones, impairs detection. The

authors concluded that detection is better when deception can be heard and worsewhen it can be seen.4 Recent experiments in computer-mediated deception point to

similar results under conditions where targets of deception rendered judgmentsfollowing extended interaction (e.g., Boyle & Ruppel, 2003; Burgoon et al., 2003).

In the latter study, for example, participants discriminated best between truths andlies in the audio modality and fared worse when visual cues were present (the face-to-face modality). Accuracy was lowest in the text condition, where deceivers were

actually rated as more trustworthy than truthtellers. Accordingly, we hypothesizedthat ‘‘deception detection is more accurate with audio (verbal 1 vocal) than text

(verbal-only) or AV (verbal 1 vocal 1 visual) presentations’’ (Hypothesis 4).As regards truth detection accuracy, the paucity of empirical evidence led us to

pose as a last research question: ‘‘Does truth detection accuracy vary by modality’’(RQ3)? One possibility is that the greater detachment and tempered judgments with

text might result in less accuracy when nonverbal cues are absent than present. This

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 579

Page 9: Human Deception Detection

speculation coincides with a previous finding that video modalities are better thantext-based modalities at truth detection (Porter, Campbell, Stapleton, & Birt, 2002).

Method

Participants

The sample consisted of 51 undergraduate students at a large university in theMidwestern United States who received extra credit for participation in a study of

interviews conducted via new media. Each participant was randomly assigned toa deceptive or truthful interview to judge and to one of the three cue availability

conditions, resulting in 17 observers per condition.

Stimulus materials

The AV, audio, and text files for this study were derived from a mock theft exper-iment conducted by Burgoon and Blair (Burgoon, Blair, & Hamel, 2006; Burgoon,

Marett, & Blair, 2004). In the mock theft study, participants were randomly assignedto the role of thieves or innocent bystanders. Thieves were asked to take a wallet from

a classroom on an assigned day and then to deceive during an interview about thetheft. Innocents were simply told that a theft would take place in their classroom and

were asked to respond truthfully during the interview. Motivation was induced byoffering participants $10 if they could convince the interviewer of their innocence.

They also could win another $50 if they were the most successful at appearingcredible. (Interviews from a low-motivation condition were excluded from the stim-

ulus pool so that only motivated deception was judged.)Trained interviewers followed a structured interview protocol that began with

some preliminary questions (personal background, education, and work experien-

ces) then turned to the theft. Nine questions were modeled after the BehavioralAnalysis Interview, a procedure that is used routinely in criminal investigations

(Inbau, Reid, Buckley, & Jayne, 2001). Questions included items such as, ‘‘Didyou take the wallet?’’ ‘‘Do you know where the wallet is now?’’ ‘‘Walk me through

what happened from the time that you arrived at class until now’’ and ‘‘What do youthink should happen to [the person who took the wallet]?’’ The theft-related

responses averaged 158 words, clearly enough length to qualify as interactive.Interviews were videotaped at 30 frames per second with a Prosumer quality

Canon digital camera. It was essential that only high-quality recordings be included

so as to prevent recording artifacts influencing judgments. A total of 17 recordings(nine innocent and eight deceptive subjects) met the criteria of acceptable video and

audio quality. These videos were then converted into Windows media files for theaudio and AV conditions. The interviews were transcribed for the text condition.

One approach to conducting judgment studies is to present each observer a seriesof brief excerpts from multiple interviews. To obtain the advantages of observ-

ing a lengthier and interactive sample of behavior, we opted instead to have eachobserver judge a single interview. Like other judgment experiments, comparability

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

580 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 10: Human Deception Detection

across conditions was achieved by using the same set of interviews in each modality.Important to note is that interviewee behavior was always produced under a face-to-

face condition so that what observers heard in the audio condition or read in the textcondition was the voice and/or words that were originally also accompanied by all

the other nonverbal cues available in face-to-face circumstances. This procedureassured a valid assessment of demeanor bias because senders could utilize all theirnormal self-presentational strategies when encoding their interview replies.

Procedure

Participants reported to a computer laboratory where they were seated at a computerstation, completed a consent form, and received experimental instructions. The

instructions explained that they would be observing an interviewee being questionedabout the theft of a wallet and that interviewees would be making a plea of innocence,

regardless of whether they were innocent or guilty. The participant’s task was ‘‘todetermine whether the person that you will be observing is telling the truth abouthis/her innocence or whether the statement they are giving is deceptive.’’ They then

saw, heard, or read the interview on the computer, completed a brief Web-basedquestionnaire about the interview, were debriefed about the purpose of the study,

given credit, and thanked for their time.

Dependent measures

Participants first rated interviewee communication on information, behavior, and

image management. Information management was assessed with a multidimensionalscale developed by Burgoon, Buller, Guerrero, et al. (1996) to measure quantity

(completeness), quality, clarity, and directness/relevance of interviewee verbalresponses. Ratings were made on 24 7-point Likert-format scales (e.g., ‘‘The inter-viewee gave very brief answers’’). Coefficient alpha reliabilities were .81 for quantity,

.80 for quality, .85 for clarity, and .76 for directness. Because of high intercorrelationsamong the four dimensions (average r = .71), the four dimensions were also analyzed

unidimensionally.Behavior management consisted of 14 semantic differential items measuring

involvement and dominance that had been used in previous investigations (e.g.,Burgoon, Buller, Floyd, et al., 1996). Reliabilities were .88 for dominance and .68

for involvement.Image management was assessed with a multidimensional measure of credibility

that has been well validated in previous investigations (e.g., Burgoon, 1976;

McCroskey & Young, 1981). Coefficient alpha reliabilities for the respective di-mensions were .90 for character, .75 for competence, .78 for sociability, and .86 for

composure. The four measures were highly correlated with an average truth esti-mate: character, r(51) = .70, p , .001; competence, r(51) = .48, p , .001; compo-

sure, r(51) = .52, p , .001; and sociability, r(51) = .46, p , .001. The very largeeffect sizes indicate a strong association between general impressions of credibility

and attributions of truthfulness on specific questions. As a further estimate of

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 581

Page 11: Human Deception Detection

credibility, a ‘‘projected trust’’ measure was created consisting of four 7-pointLikert-format scales that asked observers if they would choose the interviewee as

a roommate, job candidate, house sitter for pets, or date for a friend. These fouritems were combined into a single trust measure with a reliability of .86.

To assess whether interviewee behaviors violated expectations negatively, partic-ipants completed seven expectedness and valence measures, taken from Burgoon andWalther (1990), on the 7-point Likert format. Coefficient alpha reliabilities were .76

and .78. Due to high intercorrelation (r = .84), these measures were also combinedinto a unidimensional version.

To assess bias and detection accuracy, the last part of the questionnaire askedparticipants to rate, on a 0–10 scale, how truthful they thought the interviewee was in

answering seven of the questions in the interview and to check off whether theythought the interviewee was guilty or innocent of taking the wallet. The dichotomous

measure of guilt assessed truth bias, calculated as the aggregate deviation of thedichotomous judgments from the base rate of truthful and deceptive stimuli to bejudged. Judgments were compared to actual guilt or innocence to calculate one

measure of accuracy.5 The truthfulness ratings were averaged together for a meantruth estimate. The absolute value was a second gauge of bias; the relative differences

across conditions served as a second measure of accuracy.

Results

All hypotheses were tested with alpha set at .05, one-tailed. Power for full-samplebinomial tests was .78; for tests within modalities, it was .45. Power of factorial F tests

and simple effect t tests to detect medium effect sizes (Glass’s d = .50) was approx-imately .53 for deception effects and .45 for modality effects (Kraemer & Thiemann,1987; Lenth, 2006).

Hypothesis 1: Truth bias

Hypothesis 1 predicted that observers err in the direction of judging too manymessages as truthful. On the dichotomous judgments, 67% of the participants indi-

cated that they thought that the interviewee was truthful and 33% judged the inter-viewee as deceptive. A binomial test confirmed that these estimates were significantly

different from the expected percentages of 53% and 47%, respectively (p = .004, one-tailed). On the 10-point truthfulness scale, the mean judgment was 7.58 (SD = 1.58),which was significantly higher (more truthful) than the expected median scale value

of 5.30, t(50) = 5.78, p , .001. These results support Hypothesis 1. Observers’judgments were biased in favor of truth.

Hypothesis 2: Visual bias

Hypothesis 2 predicted that the truth bias observed in Hypothesis 1 would increaseordinally with the addition of vocal and then visual cues. A planned contrast

revealed an ordinal increase in the proportion of truthful judgments across

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

582 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 12: Human Deception Detection

modalities, t(48) = 2.23, p , .05. Judgments of truth (innocence) increased ordi-nally from 47% with the text presentation to 71% with the addition of vocal cues to

82% with the addition of visual cues. (Binomial tests conducted within eachmodality confirmed that judgments of truthfulness in the visual and vocal con-

ditions, respectively, were significantly different than the expected value, p = .003and p = .043, one-tailed; the text condition did not differ from the expected value.)

A repeated measures analysis of variance on the truthfulness ratings for the three

theft-specific questions produced a near-significant main effect for modality, F(2,45) = 3.07, p = .056, partial h2 = .12. A planned contrast with lambda coefficients of

21, 0, and 11 was significant, t(48) = 2.46, p = .009, one-tailed. The mean truthestimates on the 10-point scale were 8.01 (SD = 2.28) for the AV condition, 7.03

(SD = 1.98) for the audio condition, and 6.25 (SD = 2.17) for the text condition.Taken together, these analyses support Hypothesis 2. Truth bias was greatest when

visual cues were present.

Hypothesis 3 and RQ1: Demeanor biases

Hypothesis 3 predicted that demeanor bias, measured as (a) information manage-ment, (b) behavior management, and (c) image management, would increase ordi-

nally with the addition of vocal and then visual nonverbal cues. RQ1 asked if theserelationships are moderated by deception. Information management was initially

tested with the composite measure. A 2 3 3 analysis of variance produced a maineffect for modality, F(2, 51) = 5.05, p = .011, partial h2 = .18, which was qualified by

a modality by deception interaction, F(2, 51) = 4.34, p = .019, partial h2 = .16.Follow-up univariate analyses on the four separate dimensions produced significant

main effects on all dimensions except directness and modality by deception inter-actions on quality and directness. Although the overall pattern showed the hypoth-esized ordinal increase (text, M = 4.14; audio, M = 4.59, AV, M = 5.33), the patterns

differed within truth and deception. Under truth, the ordering from highest to lowestwas audio then AV then text. Under deception, AV was higher than text and audio,

as confirmed by a simple effect test using contrast codes of 21, 0, and 11, t(21) =3.33, p = .003. Thus, the general trends conformed to Hypothesis 3a—interviewees

were perceived as increasingly complete, truthful, clear, direct, and relevant with theaddition of nonverbal cues—but deception moderated results. The patterns for each

of the four dimensions can be seen in Figures 1a through 1d. See Table 1 for all means.Multivariate analysis of the behavioral management dimensions of involvement

and dominance produced a significant interaction between modality and deception,

Wilk’s l = .74, F(4, 88) = 3.55, p = .010, partial h2 = .14, and a nonsignificant maineffect, Wilk’s l = .86, F(4, 88) = 1.74, p = .148, partial h2 = .07. Univariate analyses

also produced significant interactions for both measures and a main effect for dom-inance. As seen in Figures 1e and 1f, the predicted ordinal increase held true in the

deception condition but not the truth condition. Simple effect tests within deceptionwere significant for both involvement, t(21) = 3.60, p , .001, one-tailed, and dom-

inance, t(21) = 4.29, p , .001, one-tailed.

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 583

Page 13: Human Deception Detection

ModalityAVAudioText

Mea

n R

atin

g

7.06.56.05.55.04.54.03.53.02.52.01.51.0

Deception

TruthDeception

(a)Quality

ModalityAVAudioText

Mea

n R

atin

g

7.0

6.0

5.0

4.0

3.0

2.0

1.0

(b)

Deception

TruthDeception

Quantity

ModalityAVAudioText

7.06.56.05.55.04.54.03.53.02.52.01.51.0

Mea

n R

atin

g

(c)

Deception

TruthDeception

Clarity

ModalityAVAudioText

Mea

n R

atin

g7.06.56.05.55.04.54.03.53.02.52.01.51.0

(d)

Deception

TruthDeception

Directness

ModalityAVAudioText

Mea

n R

atin

g

7.06.56.05.55.04.54.03.53.02.52.01.51.0

(e)

Deception

TruthDeception

Involvement

ModalityAVAudioText

Mea

n R

atin

g

7.06.56.05.55.04.54.03.53.02.52.01.51.0

(f)

Deception

TruthDeception

Dominance

Figure 1 Continued on next page.

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

584 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 14: Human Deception Detection

ModalityAVAudioText

Mea

n R

atin

g

7.06.56.05.55.04.54.03.53.02.52.01.51.0

(h)

Deception

TruthDeception

Character

ModalityAVAudioText

Mea

n R

atin

g

7.06.56.05.55.04.54.03.53.02.52.01.51.0

(g)

Deception

TruthDeception

Projected Trust

(j)Sociability

Mea

n R

atin

g

ModalityAVAudioText

7.06.56.05.55.04.54.03.53.02.52.01.51.0

Deception

TruthDeception

(i)

ModalityAVAudioText

Mea

n R

atin

g7.06.56.05.55.04.54.03.53.02.52.01.51.0

Competence

Deception

TruthDeception

ModalityAVAudioText

Mea

n R

atin

g

7.06.56.05.55.04.54.03.53.02.52.01.51.0

(k) Composure

Deception

TruthDeception

Figure 1 Effects of deception and modality on information management dimensions of (a)

quality, (b) quantity, (c) clarity, and (d) directness; behavior management dimensions of (e)

involvement and (f) dominance; and image management dimensions of (g) projected trust,

(h) character, (i) competence, (j) sociability, and (k) composure.

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 585

Page 15: Human Deception Detection

The analyses for image management produced a multivariate modality by decep-

tion interaction on the five credibility measures, F(8, 84) = 2.24, p = .032, partialh2 = .18, and a near-significant main effect, F(8, 84) = 1.78, p = .093, partial h2 = .15.

As with information and behavior management, the deception condition, but not thetruth condition, conformed to the predicted ordinal increase from text to audio

to AV, as confirmed by simple effect tests: character, t(21) = 3.78, p , .001; com-petence, t(21) = 2.60, p = .009; sociability, t(21) = 4.43, p , .001; composure,

t(21) = 2.64, p = .007 (all one-tailed). Deceivers actually earned higher credibilityratings than did truthtellers under AV. Comparatively, truthtellers earned highest

ratings under audio. A univariate analysis of projected trust produced only a sig-nificant main effect for modality, F(2, 51) = 18.05, p , .01, partial h2 = .45, andconformed to predictions.

In sum, perceptions of strategic communication increased with the addition ofnonverbal channels of information when interviewees were deceptive but not when

interviewees were truthful. Truthtellers regularly were judged most favorably in theaudio presentation, that is, when judges had access to verbal and vocal cues. By

contrast, deceiver communication was judged as the most complete, truthful, clear,direct, relevant, and dominant, and deceivers themselves were judged as the most

trustworthy, sociable, competent, and composed in the AV presentation, that is,when judges had access to the additional cues. When judges only had verbal infor-mation, the same deceivers received the lowest ratings. (An exception was that

deceivers earned a higher projective trust rating than truthtellers in both the AVand the text modalities, indicating that in both of these modalities, receivers are at

risk of being deluded.) These combined results are strongly supportive of deceiversbenefiting from the addition of visual nonverbal cues, in line with the demeanor bias

Table 1 Means and Standard Deviations for All Dependent Measures,

by Modality and Deception

Deception Truth

Text Audio FtF Text Audio FtF

M SD M SD M SD M SD M SD M SD

Truth estimate 6.75 2.38 6.04 1.93 8.63 2.34 5.81 2.01 7.93 1.65 7.48 2.22

Information management 3.93 1.19 3.97 1.03 5.82 1.19 4.35 0.93 5.21 0.91 4.85 1.32

Dominance 3.51 0.87 4.31 0.86 5.09 0.36 4.16 1.05 4.44 0.77 3.96 0.89

Involvement 3.50 0.85 4.75 0.77 5.00 0.87 4.59 1.04 4.48 0.78 4.19 1.00

Expectedness & valence 3.92 1.03 4.26 1.22 5.71 0.69 4.13 1.31 5.17 1.10 4.81 1.29

Character 3.72 1.06 4.53 0.53 5.38 0.94 3.86 0.79 5.31 1.16 4.42 1.59

Sociability 3.75 1.18 4.56 0.82 5.81 0.73 4.89 0.87 5.31 1.04 4.58 0.79

Composure 3.43 1.36 4.60 1.25 5.03 1.01 3.71 0.96 4.80 1.44 4.20 1.11

Competence 3.56 1.50 4.63 0.58 4.88 0.69 4.00 1.50 4.61 1.27 4.11 0.86

Projected trust 2.78 1.37 3.59 0.67 5.03 1.08 2.47 1.13 4.39 1.03 4.50 0.89

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

586 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 16: Human Deception Detection

hypothesis. That the pattern was restricted to deceivers implies that deceivers weremore proactive than truthtellers in managing their demeanor.

Research question 2: Expectancy violations bias

RQ2 asked if deception and modality interact to affect expectedness and valencejudgments. Univariate analysis of variance produced a significant modality maineffect on the combined expectedness and valence measure, F(2, 51) = 5.03,

p = .01, partial h2 = .18, and a near-significant interaction effect between modalityand deception, F(2, 51) = 2.78, p = .07, partial h2 = .11. Again, the deception

condition showed the ordinal increase from text to audio to AV, but the truthcondition did not. To truly analyze whether negative violations were perceived,

expectedness needs to be crossed with valence, as shown in Figure 2, where the six

3.50

4.00

4.50

5.00

5.50

6.00

Val

ence

4.00 4.50 5.00 5.50

Expectedness

Condition

Audio/Deception

Audio/Truth

Text/Deception

Text/Truth

Video/Deception

Video/Truth

Negative Violation Negative Confirmation

Positive Confirmation

Figure 2 Expectedness and valence of deception by modality conditions.

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 587

Page 17: Human Deception Detection

experimental conditions are arrayed. The left-hand quadrants represent unexpectedbehaviors; the right-hand quadrants represent expected behavior. The upper quad-

rants represent positively valenced behaviors; the bottom quadrant represents neg-atively valenced behaviors. The graph indicates that observers were most favorable

toward deceptive interviewees when they had full visual, vocal, and verbal access,rating them higher than all other interviewees, including truthtellers, on valence andexpectedness. This result is consistent with the results for demeanor bias. Compar-

atively, ratings were sufficiently low for deceivers in text-based and audio presenta-tions to qualify as negative violations; truthtellers under text also received ratings

that qualified as negative violations.

Hypothesis 4: Detection accuracy

Hypothesis 4 predicted that detection of deception would be the most accurate in the

audio condition and lower in the text and AV conditions. RQ3 asked if deceptioninteracts with modality to affect accuracy. The results are best understood against thebackdrop of the overall accuracy, which was 47%. By deception condition, only 29%

of actual deceptive interviews were judged as deceptive (71% false negatives) and63% of truthful interviews were judged as truthful (37% false positives). The overall

accuracy and deception detection rates are markedly different from the 54 and 47%rates reported in the Bond and DePaulo (2006) meta-analysis, though only the latter

approaches statistical significance (binomial test p = .056, one-tailed).The dichotomous measure, when analyzed by modality, revealed that observers

in the audio and text conditions were correct in judging 38% of the deceptiveinterviewees as guilty, whereas in the AV condition, only 13% of the guilty parties

were correctly judged as deceptive. These differences, however, failed to achievestatistical significance, x2(2) = 1.61, p = .45. The pattern of means for the overallaccuracy rates (i.e., including truth detection accuracy) conformed to predictions—

35% accuracy in text, 59% in audio, and 47% in AV—but also failed to achievestatistical significance, x2(2) = 1.89, p = .39.

Analysis of the truth estimate data produced a near-significant deception bymodality interaction, F(2, 45) = 2.76, p = .07, partial h2 = .11. Simple effect tests

within each modality produced a significant difference in truth and deception ratingswithin the audio condition, t(15) = 1.75, p = .05, one-tailed, but not in the text and

AV conditions (see Figure 3). In fact, the deception condition means were actuallyhigher than the truth condition means in the latter two conditions. Hypothesis 4 thusreceived limited support and RQ3 was answered with a partial yes.

Discussion

This investigation is important in several respects. First, unlike most previous judg-

ment studies, biases and detection accuracy were examined under fully interactiveconditions. Use of lengthier interviews as stimuli availed observers (as well as send-

ers) of the dynamic adjustments that characterize extended discourse and that might

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

588 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 18: Human Deception Detection

reveal deceptive intentions. As well, the stimuli were drawn from dialogic rather than

monologic responses. As postulated in IDT, the presence of natural discursive turn-taking permits senders opportunities to adapt strategically to their interlocutor,

improve their self-presentations, and evade detection (Burgoon et al., 2001). Suchadaptations would have been absent in less interactive or more abbreviated

responses. Second, this is the first investigation to examine multiple cognitive biasesin the same experiment so that their relationships to one another and to multipleoutcome measures could be assessed. Because each judge viewed a single interview

rather than a series of excerpts, it was possible to collect from them more extensivedependent measures, including both deception-related and credibility-related out-

comes and to illuminate the close interconnection between deceit and the moresuperordinate construct of credibility. Finally, this work is germane to new media,

specifically to social information processing in computer-mediated communication.Insights into how people assess text-based as compared to multimodal messages can

advance understanding of differential uses and responses to computer-mediatedmodes of communication such as e-mail, text chat, or audioconferencing.

Cognitive biases

The human ability to accurately judge another’s veracity is often sabotaged by cog-

nitive biases. The current investigation confirmed the presence of truth, visual,demeanor, and expectancy violations biases that enabled deceivers to evade detection.

These same biases that are responsible for poor deception detection also contribute tomessage senders being judged as trustworthy, competent, sociable, and composed,

thus also enlightening what information processing patterns foster credibility.

ModalityAVAudioText

Est

imat

ed M

arg

inal

Mea

ns

10

8

6

4

2

0

Deception

TruthDeception

Figure 3 Effects of deception and modality on truth estimates.

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 589

Page 19: Human Deception Detection

Observers showed a marked tendency to bias judgments in favor of truth. Com-pared to the 53% of all stimuli that were actually truthful, observers judged 67% to

be truthful, and the average truth estimate was far above the midpoint of the scale.These results reinforce what has been a consistent finding in the literature, namely,

that people are highly inclined to trust the communication of others and unlikely toquestion those judgments unless faced with some major deviation that triggersa reevaluation. The current findings extend this conclusion to messages generated

under fully interactive conditions.According to media richness theory and social information processing theory

(Daft & Lengel, 1984, 1986; Walther & Parks, 2002), differences in availability ofsocial information in different channels should affect deception detection. Text-

based messages and transcripts only avail the receiver of verbal information (savefor efforts to add in ‘‘nonverbal’’ information through such features as capitalization

and emoticons). Auditory channels add vocalic cues. AV modalities add kinesic,proxemic, physical appearance, and (sometimes) environmental information. Wehypothesized that observers judging an AV presentation would exhibit the most

visual and demeanor biases, that is, the truth bias would be most aggravated inthe AV condition, and the AV condition would be most associated with strategic

manipulation of message content, style, and overall demeanor. Results bore out ourpredictions, especially for deceivers. The truth bias was intensified by modalities that

gave observers access to nonverbal cues. Despite the fact that the same verbal contentwas present in all three modality conditions, the addition of nonverbal vocal and

visual cues increasingly led observers to judge senders’ interview answers as truthful.Following IDT postulates of strategic communication by deceivers, we also hypoth-

esized that observers would succumb to a demeanor bias with increasing availability ofnonverbal social cues. Results confirmed that deceivers’ (but not truthtellers’) overallcommunication was judged more favorably on measures of information, behavior, and

image management with increasing availability of nonverbal cues. The communicationof deceptive interviewees was seen as the most complete, honest, clear, direct/relevant,

involved, dominant, credible, trustworthy, expected, and positively valenced in the AVcondition. The demeanor bias is only valid to the extent that an honest-appearing

presentation leads observers to make faulty attributions about another’s veracity; thatis, there must be differences between truthtellers and deceivers or else the ‘‘bias’’ devolves

to a straight social skills variable in which some people are more skillful communicatorsthan others. Had we found the same pattern of behavior for both truthtellers anddeceivers, we would have been left with questionable support for the demeanor bias.

However, the repeated interactions between deception and modality and associateddifferential patterns across modalities for deceivers versus truthtellers imply that judg-

ments were not exclusively a function of structural modality features per se but also ofthe self-presentations that deceivers were able to craft using all the kinesic, physical

appearance, proxemic, and vocalic features at their disposal. Deceivers elicited ordinalincreases in favorability from the text to the audio to the AV condition, whereas truth-

tellers elicited a nonmonotonic pattern such that favorability was highest under audio.

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

590 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 20: Human Deception Detection

These results further imply that deceivers’ visual presentation was a major focusof their strategic efforts, and those efforts succeeded in winning more favorable

assessments from observers, inasmuch as in the AV modality, deceivers earnedhigher ratings than truthtellers on all measures. In the audio modality, the reverse

was true: Truthtellers earned higher ratings than deceivers on virtually all measures(except involvement, dominance, and competence). In the text modality, most judg-ments likewise favored truthtellers over deceivers, although deceivers were rated as

most truthful and worthy of future trust.The full complexion of the findings, then, points to the visual modality as the

most likely to elicit judgments favorable to deceivers. Advocates of increasing band-width in new technologies to give participants full multimodal access may, ironically,

confer advantages on deceivers. Instead of improving social presence, which suchmoves are intended to foster, they may simply reduce people’s ability to detect

another’s insincerity, ulterior motives, or deceit. Comparatively, use of leaner modal-ities may offer the best prospect for inhibiting biased information processing.

Future research on visual biasing could productively examine three additional

factors. One is the degree of vividness of visual stimuli, which could affect the extentto which they galvanize attention. A second is whether the continuous presence of

static and slow signals (such as one’s physical appearance and posture) permits deeperand repeated scrutiny as compared to dynamic and transitory vocal signals that must

be processed in real time and are then gone. A third is the proportion of reliable versusunreliable indicators within the total stimulus pool. If a disproportionate amount of

incorrect cues are present due to senders’ efforts to manage their visual presentations,then the addition of visual cues should introduce error. This is essentially the dis-

traction argument advanced by Stiff et al. (1989) that receivers are distracted by thevisual cues and so ignore more reliable cues available in other channels.

As regards the expectancy violations bias, we hypothesized that atypical behav-

iors would lead to deceivers’ communication being judged as a negative violation.The results were only partially supportive. Deception under both text and audio

conditions was judged as a negative violation, which implies that deceptive perform-ances can give themselves away by their departures from normative standards for

content, language, and voice. Were these the only conditions to qualify as expectancyviolations, we would regard the hypothesis as largely supported. However, the truth-

ful responding via text was also among the least expected and desirable combina-tions. This finding bolsters claims elsewhere about the likely dampening of feelingsof involvement, connection, and trust associated with text-based communication

(Burgoon, Bonito, & Kam, 2006). At the same time, this finding confirms that theexpectancy violations bias is not confined to communicative behavior but may also

be applicable to communication channels over which such behavior is transmitted.The results for the deception/AV condition place a further qualification on the

expectancy violations bias. Communication in this condition was judged to be themost normal and positively valenced of any of the combinations, that is, it was

a positive confirmation. This makes sense when considered within the context of

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 591

Page 21: Human Deception Detection

the demeanor bias results. Such findings could only be obtained if deceivers weremore successful than truthtellers in promulgating an attractive image in the AV

condition and if adding visual nonverbal cues enhanced their demeanor relative tothe exact same performances in the audio and text conditions. At the same time, the

results indicate that abnormal behavior by itself is not the only basis for biasedjudgment; behavior that is judged as exceedingly normal and appropriate can alsolead to biased judgment.

The expectancy violations results demonstrate the utility of arraying communi-cative behavior and modalities according to expectations and evaluations. Yet, they

also raise questions about whether negatively valenced, unexpected behavior shouldbe regarded as a bias, inasmuch as only the text but not the audio condition pro-

duced detection inaccuracies. Put differently, negative violations can be quite diag-nostic under the correct conditions (Bond et al., 1992). They can alert receivers to

anomalies that are in fact sound indicators that something is amiss. Like positiveconfirmations, they are only biasing to the extent that observers attend to the wrong,stereotypic indicators rather than to diagnostic ones. The inaccuracies in the AV

condition are a reminder as well that expected behaviors can also lead to erroneousjudgments.6

Detection accuracy

The generally poor ability of receivers to detect deception in this study is consistentwith previous research. The poor detection accuracy rates overall (47%) and within

the deception condition (29%) suggest that detectability may even worsen whenjudging messages generated interactively. Detection accuracy was also somewhat

sensitive to modality. On the continuous measure of truthfulness (but not a dichot-omous one), observers accurately discriminated truthful from deceptive intervieweeswhen in the audio condition. Their counterparts in the text and AV conditions did

not succeed in making such discriminations. In fact, observers showed a tendency toregard deceptive interviews as more truthful than truthful ones in the nonverbally

leanest and richest conditions. This pattern of findings supports the hypothesizedaccuracy of deception detection when observers have access only to audio (and

verbal) information.Our findings that truth bias and accuracy vary by modality have important

ramifications for the detection of deception. It appears that false-positive andfalse-negative rates can vary by modality without having a large impact on accuracy.It may be that the biases inherent in different modalities would make certain modal-

ities preferable for different detection tasks. For example, our criminal justice systemvalues protection of the innocent; therefore, this system would want as few false

positives as possible. The truth bias inherent in the AV condition might reinforce itsdesirability for courtroom use. A low false-negative rate might be desired in other

circumstances. For example, a single error in intelligence analysis could have pro-found implications for national security. Thus, the reduced truth bias found in text

or audio conditions might be preferable for intelligence assessment tasks. In light of

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

592 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 22: Human Deception Detection

the high rate of detection accuracy in the audio condition, audio detection mayrepresent the best of all options and has the further advantage of requiring less

investment in bandwidth for the messages being transmitted. Be it first responders,police detectives, job recruiters, or friends unmasking lies by friends, use of a voice-

only modality such as the telephone for questioning might prove to be more advan-tageous than a face-to-face confrontation.

A theory of nonverbal cue availability deception detection

A wealth of empirical evidence now documents that social information processing

and ability to detect deception vary according to access to nonverbal channels ofinformation. Can a single theory account for these effects? Probably not. Modalities

have multiple influences on sender behavior and receiver perception. That said, wepropose that a strategic communication perspective supplies a partial explanation in

that visual media present receivers with a preponderance of well-practiced andmanaged sender behaviors intended to produce a credible front. The sheer amountof social information to be processed also can result in erroneous judgments.

Media that only afford access to senders’ words reduce the processing task forreceivers and include some useful linguistic indicators of deceit, but again the pre-

ponderance of cues is likely to be deliberate, especially if senders are motivated andhave had opportunities to plan, rehearse, or edit their responses. In between are

audio modalities that add to verbal cues a mix of highly diagnostic and less con-trolled vocal cues. The greater proportion of diagnostic indicators, coupled with

some diminution in the truth bias, would account for the better discriminationbetween truth and deception in the audio condition. Observers’ recognition of

expectancy-violating deceptive behaviors in this condition is consistent with thisinterpretation.

To conclude, deception detection is a complex task that is fraught with cognitive

biases. Nonverbal cues, especially visual ones, lead detectors astray. Detectors canimprove their accuracy by attending more closely to vocal information and relying

upon audio modalities to discriminate between truth and deception. Continuedexploration of when biases are most pronounced and what can mitigate them will

aid not only in better detection of deception but also better understanding of howhumans come to trust the veracity of others.

Notes

1 Interactivity was coded for 50 studies. It was defined as senders not interacting if lying

while alone or to a passive observer; all other cases were deemed interactive. Less than

9% of the pairwise comparisons that were analyzed came from cases where senders

interacted with the person who was to judge their veracity. The vast majority came from

cases where senders told their lies to someone else (58%), such as giving a single reply to

an interviewer, or where they did not interact with anyone (33%). Median length of

sender messages was brief at 52 seconds.

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 593

Page 23: Human Deception Detection

2 In the Bond and DePaulo (2006) meta-analysis, judgments of truthfulness from within-

study comparisons follow a different ordering, with video-only messages judged as less

truthful than audio-only, AV, or text messages. We surmise that the absence of any

verbal content upon which to base a veracity judgment in the video-only condition

resulted in indecision or neutrality.

3 It should be noted that unlike other biases, demeanor bias derives not from a cognitive

proclivity among receivers but rather from features of the sender’s communication that

systematically elicit biased judgments.

4 Previous meta-analyses and studies (Burgoon, 2005; DePaulo et al., 1980; Zuckerman

et al., 1981) have reported different orderings of conditions.

5 Truth bias has been measured in a variety of ways. For example, Burgoon and colleagues

(Burgoon et al., 1994, 2003; Dunbar, Ramirez, & Burgoon, 2003) have measured bias as

the deviation of receiver estimates of truthfulness from sender reports of actual truth-

fulness such that a positively signed score reflected truth bias and a negatively signed

score, a lie bias. McBurney and Comadena (1992) measured truth bias as the extent to

which the average truthfulness rating across multiple trials of truths and lies fell toward

the high end of the rating scale. Here, we opted for objective comparison to the sample

base rate.

6 Per signal detection theory, bias is generally considered to be independent from

accuracy. That is to say, one can achieve the same accuracy level while showing very

different biases. For example, imagine a sample of materials in which 50% of the

materials are truthful and 50% are deceptive. One could obtain 50% accuracy while

exhibiting either a complete truth bias (e.g., all materials judged as truthful) or

complete deception bias (e.g., all materials judged as deceptive). Thus, varying bias

scores are compatible with a variety of accuracy scores in samples that are roughly

balanced such that increased bias may accompany increased accuracy or decreased

accuracy (Swets, 2000).

References

Afifi, W. A., & Weiner, J. A. (2004). Toward a theory of motivated information management.

Communication Theory, 14, 167–190.

Anolli, L., Balconi, M., & Ciceri, R. (2003). Linguistic styles in deceptive communication:

Dubitative ambiguity and elliptic eluding in packaged lies. Social Behavior and Personality,

31, 687–710.

Atoum, A. O., & Al-Simadi, F. A. (2000). The effect of presentation modality on judgments of

honesty and attractiveness. Social Behavior and Personality, 28, 269–278.

Bauchner, J. E., Kaplan, E. P., & Miller, G. R. (1980). Detecting deception: The relationship

between available information to judgmental accuracy in initial encounters. Human

Communication Research, 6, 251–264.

Bond, C. F., Jr., & DePaulo, B. M. (2006). Accuracy of deception judgments. Review of

Personality and Social Psychology, 10, 214–234.

Bond, C. F., Jr., Kahler, K. N., & Paolicelli, L. M. (1985). The miscommunication of

deception: An adaptive perspective. Journal of Experimental Social Psychology, 21,

331–345.

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

594 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 24: Human Deception Detection

Bond, C. F., Jr., Omar, A., Pitre, U., Lashley, B. R., Skaggs, L. M., & Kirk, C. T. (1992).

Fishy-looking liars: Deception judgment from expectancy violation. Journal of Personality

and Social Psychology, 63, 969–977.

Boyle, R. J., & Ruppel, C. P. (2003). The impact of media richness, suspicion, and perceived truth

bias on deception detection. Proceedings of the 36th annual Hawaii International

Conference on System Sciences, Big Island, HI. Los Alamitos, CA: IEEE.

Buller, D. B., & Burgoon, J. K. (1994). Deception: Strategic and nonstrategic communication.

In J. A. Daly & J. M. Wiemann (Eds.), Strategic interpersonal communication

(pp. 191–223). Hillsdale, NJ: Erlbaum.

Buller, D. B., & Burgoon, J. K. (1996). Interpersonal deception theory. Communication

Theory, 6, 203–242.

Buller, D. B., Burgoon, J. K., White, C. H., & Ebesu, A. S. (1994). Interpersonal deception: VII.

Behavioral profiles of falsification, concealment, and equivocation. Journal of Language

and Social Psychology, 13, 366–395.

Buller, D. B., Strzyewski, K. D., & Hunsaker, F. G. (1991). Interpersonal deception: II. The

inferiority of conversational participants as deception detectors. Communication

Monographs, 58, 25–40.

Burgoon, J. K. (1976). The ideal source: A reexamination of source credibility measurement.

Central States Speech Journal, 27, 200–206.

Burgoon, J. K. (1983). Nonverbal violations of expectations. In J. Wiemann & R. Harrison

(Eds.), Nonverbal interaction: Vol. 11. Sage annual reviews of communication (pp. 11–77).

Beverly Hills, CA: Sage.

Burgoon, J. K. (1985). The relationship of verbal and nonverbal codes. In B. Dervin &

M. J. Voight (Eds.), Progress in communication sciences (pp. 263–298). Norwood, NJ:

Ablex.

Burgoon, J. K. (1994). Nonverbal signals. In M. L. Knapp & G. R. Miller (Eds.), Handbook of

interpersonal communication (2nd ed., pp. 344–390). Beverly Hills, CA: Sage.

Burgoon, J. K. (2005). The future of motivated deception detection. In P. Kalbfleisch (Ed.),

Communication yearbook 29 (pp. 49–95). Mahwah, NJ: Erlbaum.

Burgoon, J. K., Blair, J. P., & Hamel, L. (2006, June). Factors influencing deception detection:

Impairment or facilitation? Paper presented to the annual meeting of the International

Communication Association, Dresden, Germany.

Burgoon, J. K., Bonito, J. A., Bengtsson, B., Ramirez, A., Jr., Dunbar, N., & Miczo, N.

(1999–2000). Testing the interactivity model: Communication processes, partner

assessments, and the quality of collaborative work. Journal of Management Information

Systems, 16(3), 33–56.

Burgoon, J. K., Bonito, J. B., & Kam, K. (2006). Communication and trust under face-to-face

and mediated conditions: Implications for leading from a distance. Manuscript submitted

for publication.

Burgoon, J. K., & Buller, D. B. (2004). Interpersonal deception theory. In J. S. Seiter &

R. H. Gass (Eds.), Readings in persuasion, social influence and compliance-gaining

(pp. 239–264). Boston: Allyn & Bacon.

Burgoon, J. K., Buller, D. B., Ebesu, A. S., & Rockwell, P. (1994). Interpersonal deception:

V. Accuracy in deception detection. Communication Monographs, 61, 303–325.

Burgoon, J. K., Buller, D. B., & Floyd, K. (2001). Does participation affect deception success?

A test of the inter-activity effect. Human Communication Research, 27, 503–534.

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 595

Page 25: Human Deception Detection

Burgoon, J. K., Buller, D. B., Floyd, K., & Grandpre, J. (1996). Deceptive realities: Sender,

receiver, and observer perspectives in deceptive conversations. Communication Research,

23, 724–748.

Burgoon, J. K., Buller, D. B., Guerrero, L., Afifi, W., & Feldman, C. (1996). Interpersonal

deception: XII. Information management dimensions underlying deceptive and truthful

messages. Communication Monographs, 63, 50–69.

Burgoon, J. K., Buller, D. B., White, C. H., Afifi, W., & Buslig, A. L. S. (1999). The role of

conversational involvement in deceptive interpersonal interactions. Personality and Social

Psychology Bulletin, 25, 669–686.

Burgoon, J. K., & Burgoon, M. (2001). Expectancy theories. In P. Robinson & H. Giles (Eds.),

Handbook of language and social psychology (2nd ed., pp. 79–101). Sussex, UK: John Wiley

& Sons.

Burgoon, J. K., Marett, K., & Blair, J. P. (2004). Detecting deception in computer-mediated

communication. In J. F. George (Ed.), Computers in society: Privacy, ethics & the Internet

(pp. 154–166). Upper Saddle River, NJ: Prentice-Hall.

Burgoon, J. K., Stoner, G. M., Bonito, J. A., & Dunbar, N. E. (2003, January). Trust and

deception in mediated communication. Proceedings of the 36th Annual Hawaii

International Conference on System Sciences. Big Island, HI. Los Alamitos, CA: IEEE.

Burgoon, J. K., & Walther, J. B. (1990). Nonverbal expectancies and the consequences of

violations. Human Communication Research, 17, 232–265.

Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source

versus message cues in persuasion. Journal of Personality & Social Psychology, 39, 752–766.

Clark, H., & Clark, E. (1977). Psychology and language. New York: Harcourt Brace Jovanovich.

Daft, R. L., & Lengel, R. H. (1984). Information richness—A new approach to managerial

behavior and organization design. Research in Organizational Behavior, 6, 191–233.

Daft, R. L., & Lengel, R. H. (1986). Organizational information, media richness and structural

design. Management Science, 32, 554–571.

DePaulo, B. M. (1992). Nonverbal behavior and Self-presentation. Psychological Bulletin, 111,

203–243.

DePaulo, B., Lindsay, J., Malone, B., Muhlenbruck, L., Charlton, K., & Cooper, H. (2003).

Cues to deception. Psychological Bulletin, 129, 74–118.

DePaulo, B. M., & Rosenthal, R. (1979). Ambivalence, discrepancy, and deception. In

R. Rosenthal (Ed.), Skill in nonverbal communication: Individual differences (pp. 204–248).

Cambridge, MA: Oelgeeschlager, Gunn & Hain.

DePaulo, B. M., Rosenthal, R., Green, C. R., & Rosenkrantz, J. (1982). Diagnosing deceptive

and mixed messages from verbal and nonverbal cues. Journal of Experimental Social

Psychology, 18, 433–446.

DePaulo, B. M., Zuckerman, M., & Rosenthal, R. (1980). Detecting deception: Modality

effects. In L. Wheeler (Ed.), Review of personality and social psychology (pp. 125–162).

Beverly Hills, CA: Sage.

Dunbar, N. E., Ramirez, A., Jr., & Burgoon, J. K. (2003). Interactive deception: Effects of

participation on participant-receiver and observer judgments. Communication Reports,

16, 23–33.

Ekman, P., & Friesen, W. V. (1974). Detecting deception from the body or face. Journal of

Personality and Social Psychology, 29, 288–298.

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

596 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Page 26: Human Deception Detection

Feldman, R. S. (1976). Nonverbal disclosure of teacher deception and interpersonal affect.

Journal of Educational Psychology, 68, 807–816.

Fiedler, K. (1993). Training lie detectors to use nonverbal cues instead of global heuristics.

Human Communication Research, 20, 199–223.

Fiske, S. T. (1993). Social cognition and social perception. Annual Review of Psychology,

44, 155–194.

Fiske, S. T., & Taylor, S. E. (1991). Social cognition (2nd ed.). New York: McGraw-Hill.

Gilbert, D. T., Krull, D. S., & Malone, P. S. (1990). Unbelieving the unbelievable: Some

problems in the rejection of false information. Journal of Personality and Social Psychology,

59, 601–613.

Gilbert, D. T., Pelham, B. W., & Krull, D. S. (1988). On cognitive busyness: When person

perceivers meet person perceived. Journal of Personality and Social Psychology, 54,

733–740.

Green, D. M., & Swets, J. A. (1966). Signal detection theory and psychophysics. New York:

Wiley.

Grice, P. (1989). Studies in the way of words. Cambridge, MA: Harvard University Press.

Hocking, J. E., Bauchner, J., Kaminski, E. P., & Miller, G. R. (1979). Detecting deceptive

communication from verbal, visual, and paralinguistic cues. Human Communication

Research, 6, 33–46.

Inbau, F. E., Reid, J. E., Buckley, J. P., & Jayne, B. P. (2001). Criminal interrogations and

Confessions. Gaithersburg, MD: Aspen.

Johnson, P. E., Grazioli, S., Jamal, K., & Berryman, G. (2001). Detecting deception:

Adversarial problem solving in a low base rate world. Cognitive Science, 25, 355–392.

Kraemer, H. C., & Thiemann, S. (1987). How many subjects? Statistical power analysis in

research. Thousand Oaks, CA: Sage.

Kraut, R. E., & Higgins, E. T. (1984). Communication and social cognition. In R. S. Wyer, Jr.

& T. K. Srull (Eds.), Handbook of social cognition (Vol. 3, pp. 88–127). Hillsdale, NJ:

Erlbaum.

Lenth, R. V. (2006). Java applets for power and sample size [computer software]. Retrieved

February 12, 2007, from http://www.stat.uiowa.edu/~rlenth/Power

Levine, T. R., Kim, R., Park, H. S., & Hughes, M. (2006). Deception detection accuracy is

a predictable linear function of message veracity base-rate: A formal test of Park and

Levine’s probability model. Communication Monographs, 73, 243–260.

Levine, T. R., Park, H. S., & McCornack, S. A. (1999). Accuracy in detecting truths and lies:

Documenting the ‘‘veracity effect.’’ Communication Monographs, 66, 125–144.

McBurney, D. L., & Comadena, M. E. (1992, November). An examination of the McComack

and Parks model of deception detection. Paper presented at the annual meeting of the

Speech Communication Association, Chicago, IL.

McCornack, S. A., Levine, T. R., Morrison, K., & Lapinski, M. (1996). Speaking of

information manipulation: A critical rejoinder. Communication Monographs, 63, 83–92.

McCornack, S. A., & Parks, M. (1986). Deception detection and relationship development:

The other side of trust. In M. L. McLaughlin (Ed.), Communication yearbook 9. Beverly

Hills, CA: Sage.

McCroskey, J. C., & Young, T. J. (1981). Ethos and credibility: The construct and its

measurement after three decades. Central States Speech Journal, 32, 24–34.

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 597

Page 27: Human Deception Detection

Motley, M. T., & Camden, C. T. (1988). Facial expression of emotion: A comparison of posed

expressions versus spontaneous expressions in an interpersonal setting. Western Journal of

Speech Communication, 52, 1–22.

Noller, P. (1985). Video primacy—Another look. Journal of Nonverbal Behavior, 9, 28–47.

O’Sullivan, M. (2003). The fundamental attribution error in detecting deception: The

boy-who-cried-wolf effect. Personality and Social Psychology Bulletin, 29, 1316–1327.

O’Sullivan, M., Ekman, P., & Friesen, W. V. (1988). The effect of comparisons on detecting

deceit. Journal of Nonverbal Behavior, 12, 203–215.

Porter, S., Campbell, M. A., Stapleton, J., & Birt, A. R. (2002). The influence of judge, target,

and stimulus characteristics on the accuracy of detecting deceit. Canadian Journal of

Behavioural Science—Revue Canadienne Des Sciences Du Comportement, 34, 172–185.

Ramirez, A. Jr., & Burgoon, J. K. (2004). The effect of interactivity on initial interactions:

The influence of information valence and modality and information richness on

computer-mediated interaction. Communication Monographs, 71, 422–477.

Riggio, R. E., Tucker, J., & Throckmorton, B. (1987). Social skills and deception ability.

Personality and Social Psychology Bulletin, 13, 568–577.

Stiff, J., Kim, H., & Ramesh, C. (1992). Truth biases and aroused suspicion in relational

deception. Communication Research, 19, 326–345.

Stiff, J., Miller, G., Sleight, C., Mongeau, P., Garlick, R., & Rogan, R. (1989). Explanations for

visual cue primacy in judgments of honesty and deceit. Journal of Personality & Social

Psychology, 56, 555–564.

Swets, J. A. (2000). Signal detection theory and ROC analysis in psychology and diagnostics:

Collected papers. Mahwah, NJ: Erlbaum.

Todorov, A., Chaiken, S., & Henderson, M. D. (2002). The heuristic-systematic model of

social information processing. In J. P. Dillard & M. Pfau (Eds.), The persuasion handbook:

Developments in theory and practice (pp. 195–211). Thousand Oaks, CA: Sage

Publications.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty—Heuristics and biases.

Science, 185, 1124–1131.

Vrij, A. (2000). Detecting lies and deceit: The psychology of lying and the implications for

professional practice. New York: John Wiley.

Vrij, A., & Mann, S. (2001). Who killed my relative? Police officers’ ability to detect real-life

high stake lies. Psychology, Crime & Law, 7, 119–132.

Walther, J. B., & Parks, M. R. (2002). Cues filtered out, cues filtered in: Computer mediated

communication and relationships. Thousand Oaks, CA: Sage.

White, C. H., & Burgoon, J. K. (2001). Adaptation and communicative design: Patterns of

interaction in truthful and deceptive conversations. Human Communication Research, 27,

9–37.

Zhou, L., Burgoon, J. K., Twitchell, D., & Nunamaker, J. F., Jr (2004). Automating

linguistics-based cues for detecting deception in text-based asynchronous

computer-mediated communication. Group Decision and Negotiation, 13, 81–106.

Zuckerman, M., DeFrank, R. S., Hall, J. A., Larrance, D. T., & Rosenthal, R. (1979). Facial and

vocal cues of deception and honesty. Journal of Experimental Social Psychology, 15,

378–396.

598 Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception J. K. Burgoon et al.

Page 28: Human Deception Detection

Zuckerman, M., DePaulo, B. M., & Rosenthal, R. (1981). Verbal and nonverbal

communication of deception. In L. Berkowitz (Ed.), Advances in experimental social

psychology (Vol. 14, 1–59). New York: Academic Press.

Zuckerman, M., & Driver, R. (1985). Telling lies: Verbal and nonverbal correlates of

deception. In A. W. Siegman & S. Feldstein (Eds.), Nonverbal communication: An

integrated perspective (pp. 129–147). Hillsdale, NJ: Erlbaum.

Zuckerman, M., Larrance, D. T., Spiegel, N. H., & Klorman, R. (1981). Controlling nonverbal

displays: Facial expressions and tone of voice. Journal of Experimental Social Psychology,

17, 506–524.

Human Communication Research 34 (2008) 572–599 ª 2008 International Communication Association 599

J. K. Burgoon et al. Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Page 29: Human Deception Detection

Les biais cognitifs et la disponibilité des indices non verbaux dans la détection

du mensonge

Judee K. Burgoon, University of Arizona

J. P. Blair, Texas State University

Renee E. Strom, St. Cloud State University

Résumé

Dans les situations potentiellement trompeuses, les gens se fient sur des raccourcis mentaux afin d'aider à

traiter l'information. Ces jugements heuristiques sont souvent biaisés et ont pour résultat des évaluations

erronées de l'honnêteté de l'émetteur. Quatre de ces biais (le biais de vérité, le biais visuel, le biais

comportemental et le biais de violation des attentes) furent examinés dans une expérience de jugements

qui variait en disponibilité des indices non verbaux et en mensonge. Les observateurs ont vu un entretien

complet enregistré sur vidéo (accès complet aux indices visuels, vocaux et verbaux), entendu l'entretien

complet (accès vocal et verbal) ou lu une transcription (accès verbal) d'un suspect honnête ou trompeur,

interrogé à propos d'un faux vol. Ils ont ensuite classé l'interviewé selon des critères d'information, de

comportement, de gestion de l'image et d'honnêteté. Les résultats appuient la présence de chacun des

quatre biais, qui étaient le plus évidents lorsque les interviewés mentaient et que les observateurs avaient

accès à toutes les modalités visuelles, vocales et verbales. Avec l'ajout des indices non verbaux, les

messages des menteurs étaient jugés comme étant de plus en plus complets, honnêtes, clairs et pertinents;

leurs comportements comme étant plus complexes et dominants; leur comportement général comme plus

crédible. Les menteurs étaient en fait jugés plus crédibles que les personnes honnêtes dans la modalité la

plus complète (indices visuels, vocaux et verbaux), tandis que la plus grande exactitude dans la

discrimination et la détection s'est produite chez les gens n'ayant eu accès qu'à l'enregistrement audio. Les

résultats ont des implications pour les facteurs qui influencent les jugements de la crédibilité d'un

émetteur et l'exactitude dans la distinction entre la vérité et le mensonge, surtout dans des conditions où

les émetteurs produisent les messages de façon interactive.

Mots clés : mensonge, comportement non verbal, communication interpersonnelle, crédibilité,

confiance, modalité, CMO

Page 30: Human Deception Detection

Kognitive Befangenheit und nonverbale Hinweisverfügbarkeit beim Aufdecken von Täuschung

Judee K. Burgoon, University of Arizona

J. P. Blair, Texas State University

Renee E. Strom, St. Cloud State University

In potentiellen Täuschungssituationen greifen Menschen auf mentale Abkürzungen zurück, die

ihnen helfen, Informationen zu verarbeiten. Diese heuristischen Urteile sind oft befangen und

resultieren in einer fehlerhaften Beurteilung der Aufrichtigkeit des Senders. Vier solcher

Befangenheiten – Wahrheitsbefangenheit, visuelle Befangenheit, Verhaltensbefangenheit und

Erwartungsverletzungsbefangenheit – untersuchten wir in einem Beurteilungsexperiment mit

variierter nonverbaler Hinweisverfügbarkeit und Täuschung. Beobachter sahen ein

aufgezeichnetes Video (visueller, vokaler und verbaler Zugang), hörten ein Interview (vokaler

und verbaler Zugang) oder lasen ein Manuskript (verbaler Zugang) eines wahrheitsgemäßen oder

täuschenden Verdächtigen, der bezüglich eines Entwendungsdiebstahls verhört wurde. Danach

beurteilten die Teilnehmer diesen hinsichtlich der Informationen und Verhaltensweisen, des

Imagemanagement und der Wahrhaftigkeit. Die Ergebnisse stützen die Existenz aller vier

Befangenheiten, die sich am deutlichsten zeigten, wenn Interviewte täuschten und die

Beobachter Zugang zu allen visuellen, vokalen und verbalen Modalitäten hatten. Die Botschaft

des Täuschenden wurde als zunehmend vollständig, ehrlich, klar und relevant, sein Verhalten als

stärker involviert und dominant, und sein allgemeines Verhalten als glaubwürdiger beurteilt,

wenn nonverbale Hinweise ergänzt wurden. Täuschende wurden in der AV-Variante sogar als

glaubwürdiger beurteilt als jene, die die Wahrheit sagten. Die beste Unterscheidung und

Entdeckungsgenauigkeit herrschte in der Audio-Kondition vor. Die Ergebnisse zeigen auf,

welche Faktoren die Beurteilung der Glaubwürdigkeit eines Senders und die Genauigkeit bei der

Unterscheidung von Wahrheit und Täuschung beeinflussen; insbesondere unter Bedingungen, in

denen der Sender die Botschaft interaktiv produziert.

Page 31: Human Deception Detection

Los Prejuicios Cognitivos y La Disponibilidad de la Clave No Verbal en la

Detección del Engaño

Judee K. Burgoon, University of Arizona

J. P. Blair, Texas State University

Renee E. Strom, St. Cloud State University

Resumen

En situaciones potencialmente engañosas, la gente confía en los atajos mentales para ayudarse en

el procesamiento de información. Estos juicios heurísticos son a menudo tendenciosos y dan

como resultado evaluaciones imprecisas acerca de la veracidad del emisor. Cuatro de esos

prejuicios –prejuicio sobre la veracidad, prejuicio visual, prejuicio sobre el comportamiento, y

prejuicio sobre la violación de expectación –fueron examinados en un experimento de juicio

variando la disponibilidad de la clave no verbal y el engaño. Los observadores vieron una

entrevista completa grabada en video (con acceso pleno a las claves visuales, vocales y verbales),

escucharon la entrevista en su totalidad (acceso a lo vocal y verbal), ó leyeron una transcripción

(acceso a lo verbal) de un sospechoso veraz ó mentiroso cuestionado sobre un presunto robo,

luego clasificaron al entrevistado acerca de la información, el comportamiento, el manejo de la

imagen y la veracidad. Los resultados respaldaron la presencia de los 4 prejuicios, que fueron

más evidentes cuando los entrevistados mintieron y los observadores tuvieron acceso a las

modalidades visuales, vocales, y verbales. Los mensajes de los impostores fueron juzgados como

más completes, honestos, claros, y relevantes; sus comportamientos fueron más involucrados y

dominantes; y sus comportamientos en general fueron más creíbles, con el aditamento de las

claves no verbales. Los impostores fueron juzgados actualmente como más creíbles que aquellos

que decían la verdad en la modalidad audio visual, mientras que la mayor discriminación y

certeza de detección ocurrió en la condición auditiva. Los resultados tienen implicancias sobre

qué factores influyen los juicios sobre la credibilidad del emisor de un mensaje y la certeza para

distinguir la verdad de la mentira, especialmente bajo condiciones en la cuales los emisores

producen mensajes en forma interactiva.

Palabra claves: decepción, comportamiento no verbal, comunicación interpersonal,

credibilidad, confianza, modalidad, CMC

Page 32: Human Deception Detection

认知性偏见和非语言线索的存在性在识别欺骗中的作用

Judee K. Burgoon

亚利桑那大学

J. P. Blair

德州州立大学

Renee E. Strom

St. Cloud 州立大学

在潜在的欺骗情景中,人们依赖认知捷径来帮助处理信息。这些启发式判断

常存有偏见,造成对信息发送者之真实程度的不准确评价。将欺骗和非言语

线索之存在作为变量,本研究通过实验探讨了四种偏见,即真相偏见、视觉

偏见、表现偏见以及期望相饽偏见。实验参加者或观看全程的录像采访(可

全方位接触视觉、声觉和语言线索)、或收听全程的采访录音(可接触声觉

和语言线索)、或阅读采访的文本(可接触语言线索)。采访对象是一个被

疑有偷窃行为的人。实验参与者根据他们所接触的信息来对该采访对象的信

息、行为、形象管理和诚实程度进行评价。结果证实了上述四种偏见的存

在,其中最明显的是采访对象存在欺骗行为而观察者接触到了所有的视觉、

声觉和语言线索。随着非语言线索的添加,行骗者的信息被认为是越来越完

整、诚实、清晰和相关,他们的行为被认为是更投入且有主导性,而且他们

总体的品行被认为有更高的可信度。在听觉和视觉环境下,参加者认为行骗

者实际上比说实话者更值得信赖。在听觉环境下,则发生对欺骗最准确的判

别。研究结果有助于我们了解何种因素影响了对信息发出者之可信度的判

断,以及何种因素影响了识别真相/欺骗的准确性,尤其是在信息发送者通

过交互方式制造信息的时候。

Page 33: Human Deception Detection

사기성 발견에 있어 인지적 편견들과 비언어적 단서 유효성에 관한 연구

Judee K. Burgoon, University of Arizona

J. P. Blair, Texas State University

Renee E. Strom, St. Cloud State University

요약

잠재적으로 사기성이 있는 상황에서, 사람들은 정보전달을 돕기위해 정신적 지름길에

의존한다. 이러한 발견적인 판단들은 종종 편견적인 경우가 있으며 정보전달자의

진실성을 잘못 판단하는 경우로 이어진다. 네가지 편견들 (진실, 시각, 행위, 그리고

기대위반 편견)이 비언어적 단서 유효성과 기만을 다양화한 판단 실험하에서 연구되었다.

관찰자들은 연출된 도난에 관한 질문을 통해 진실된 또는 사기적인 혐의자들에 대하여

비디오로 촬영된 인터뷰 (시각, 목소리, 그리고 언어적 단서들에 대한 완전한 접근을

의미)를 보았으며, 완벽한 인터뷰 (목소리와 언어적 접근)를 들었으며, 또는 원고 (언어적

접근)를 읽었다. 관찰자들은 이후 정보, 행위, 이미지 관리와 진실성이라는 측면에서

인터뷰 대상자들을 등급화하였다. 결과들은 인터뷰 대상자들이 사기성이 있었고

관찰자들이 시각, 언어, 목소리, 그리고 양식에 관하여 접근할 수 있었을때 이들 4 가지

편견들 모두의 존재를 지지하였다. 사기자들의 메시지들은 점증적으로 완전하며,

진실하며, 명백하고 관련성있는 것으로 판단되었다. 그리고 그들의 행위는 비언어적

단서를 더할때 전체적으로 더욱 믿을만한 것으로 나타났다. 사기자들을 실제적으로

AV 양식에서 진실한사람들보다 더욱 신뢰할만한 것으로 판단되었다. 반면, 최적의

차별과 발견의 정확도는 오디어 상황에서 나타났다. 결과들은 사기성으로부터 진실을

구별할때 정보전달자의 신뢰성과 정확성의 판단에 영향을 미치는 요소가 무엇인지에

대한 함의를 제공하고 있는데, 특히 정보전달자가 메시지를 상호작용적으로 생산하는

상황에서 더욱 그러한 것으로 나타났다.

Page 34: Human Deception Detection