Lying Online: Examining the Production, Detection, and Popular Beliefs Surrounding Interpersonal Deception in Technologically-Mediated Environments

Telling lies often requires creating a story about an experience or attitude that does not exist. As a result, false stories may be qualitatively different from true stories. The current project investigated the features of linguistic style that distinguish between true and false stories. In an analysis of five independent samples, a computer-based text analysis program correctly classified liars and truth-tellers at a rate of 67% when the topic was constant and a rate of 61% overall. Compared to truth-tellers, liars showed lower cognitive complexity, used fewer self-references and other-references, and used more negative emotion words.

This study examines self-presentation in online dating profiles using a novel cross-validation technique for establishing accuracy. Eighty online daters rated the accuracy of their online self-presentation. Information about participants' physical attributes was then collected (height, weight, and age) and compared with their online profile, revealing that deviations tended to be ubiquitous but small in magnitude. Men lied more about their height, and women lied more about their weight, with participants farther from the mean lying more. Participants' self-ratings of accuracy were significantly correlated with observed accuracy, suggesting that inaccuracies were intentional rather than self-deceptive. Overall, participants reported being the least accurate about their photographs and the most accurate about their relationship information. Deception patterns suggest that participants strategically balanced the deceptive opportunities presented by online self-presentation (e.g., the editability of profiles) with the social constraints of establishing romantic relationships (e.g., the anticipation of future interaction).