More Than Meets the Eye: How Oculometric Behaviors Evolve Over the Course of Automated Deception Detection Interactions
研究使用潜变量增长曲线模型，分析欺骗者和诚实者在与自动化检测系统交互过程中瞳孔扩张和注视模式的变化趋势，发现欺骗者的眼动指标随时间演变的方式不同，且不受相关刺激呈现的影响。
Eye-tracking technology has exhibited promise for identifying deception in automated screening systems. Prior deception research using eye trackers has focused on the detection and interpretation of brief oculometric variations in response to stimuli (e.g., specific images or interview questions). However, more research is needed to understand how variations in oculometric behaviors evolve over the course of an interaction with a deception detection system. Using latent growth curve modeling, we tested hypotheses explaining how two oculometric behaviors—pupil dilation and eye-gaze fixation patterns—evolve over the course of a system interaction for three groups of participants: deceivers who see relevant stimuli (i.e., stimuli pertinent to their deception), deceivers who do not see relevant stimuli, and truth-tellers. The results indicate that the oculometric indicators of deceivers evolve differently over the course of an interaction, and that these trends are indicative of deception regardless of whether relevant stimuli are shown.