Deceit and Interactional Synchrony In Different Social Constellations

Humans are a social species, but the nature of the connection between any two persons varies. Typically, two friends have a stronger relationship than do two strangers. The nature of the interaction also varies depending on the messages conveyed, such as when a truth versus a lie is told. A measure that captures the fundamental social dynamics between people is called interactional synchrony, and it reflects the extent to which the behavior of two or more individuals correlates within a short time window. Past research shows that interactional synchrony strengthens a relationship. However, a cohesive synchrony measure that captures multiple facets of behavior has yet to be tested. This project explores the role of deception in interactional synchrony in three different social constellations: individuals who have built rapport with a stranger, individuals who are friends, and individuals who belong to the same social organization. The synchrony between an interviewer and an interviewee, of varying levels of social relationship, will be captured when the interviewee lies and tells the truth about an action. The research uses computer vision and machine learning techniques to analyze and uncover synchrony in the faces, vocal tones, bodies, postures, and sub-visible physiological responses of interviewers and interviewees. The results will inform the need to consider social ties in research on deceptive behavior and when assessing demeanor during real world interactions, such as interviews with criminal suspects or potential terrorists. This project explores the role of deception in interactional synchrony in three different social constellations: individuals who have built rapport with a stranger, individuals who are friends, and individuals who belong to the same social organization. Interactional synchrony is expected to be higher for interactions that involve high rapport, closer friendship, and shared group membership. The deception scenarios involve both sanctioned and unsanctioned lying. The variation in interactional synchrony as a result of lying compared to truth telling within participants and as a function of truth/lie interactions with rapport, friendship, and shared group membership will be evaluated. The analysis of synchrony using computer vision and machine learning algorithms applied to different channels, ranging from more controllable behaviors, such as posture, to those less controllable, such as electrodermal responses, will enable a global interactional synchrony measure and also aid in the understanding of interactional synchrony as a concept, separating intentional mimicry from synchrony that is more automatic and unconscious. This refinement in the measurement technology of interactional synchrony will be of special value in detecting deceit, thereby contributing to the nation's security priorities.