Digital Deception

Assignment 7, option 1: Catch Me if You Can

We know that users recognize CMC spaces to be forums for deception. Research, like the study conducted by Dhamija et al. (2006), has found that most internet users believe internet deception to be pervasive. Interestingly, however, similar studies, like the one conducted by Capsi and Gorsky (2006) have found that internet users detect deception with very low frequency. Even in a laboratory setting – where the natural inclination for individuals to believe the people with which they interact, also known as truth bias, is often diminished – George et al. (2004) found that deception detection rates over CMC are very low. There are several factors involved in deception detection in online spaces, some of which explain the low rates found in these studies.

Motivation can play a role in deception detection. Research has indicated that highly motivated liars in face-to-face media have a tendency to “leak” nonverbal cues, increasing the rate of detection. In CMC, on the other hand, high motivation frequently leads to decreased detection. In the absence of nonverbal cues and heightened control over the message that CMC affords, deceivers are more successful over CMC.

One reason for this might be those predicted by the Social Presence Theory. This theory suggests that the lack of social presence felt by receivers may prevent them from feeling that their conversation is “real.” Without feeling that their conversation has the same strength and communicative properties of face-to-face conversation, listeners and receivers cannot engage in realistic dialogue. George et al. (2006) cite a study which explains why this poses a problem for deception detection in online spaces. According to Short et al. (1976), without feeling like the conversation is real, participants cannot ascertain the veracity of the message. Because the conversation takes on an unnatural feel, receivers pay less attention to communicative partners; this negligence minimizes ability to detect deception.

Suspicion is another variable in deceptive communication. As suspicion increases, deception detection increases. George et al. (2006) found that participants given some forewarning of deception were five times more likely to correctly identify deceptive statements than were participants who were not given a warning. Interestingly, this study found an “abysmal” rate of deception detection even after study participants had been predisposed toward suspicion. This is surprising because one might expect that in an experiment setting, the truth bias would be diminished for all participants – even those who had not been given a warning. If anything, it might be predicted that in the controlled environment of an experiment, both suspicion and detection would be abnormally high.

Verbal cues also play a role in deception detection. Hancock et al. (2004) describes these cues as an increase in negative statements and use of the passive voice. The passive voice serves to distance the speaker from the lie. Rowe classifies deceptive cues into “low-level” and “high-level” or cognitive clues. Low-level verbal clues include the increased use of negative statements and passive voice along with increased hyperbole and overgenerality. High-level verbal cues to deception mainly include logical fallacies or factual inconsistencies.

Finally, Rowe also points out that hesitation – even in a text based communication – is an indication of deception. So taken together, Hancock and Rowe’s research tells us that if we want to get away with a lie, we should relay it in an online environment and type it out relatively quickly.

posted by Erica @ 3:06 AM