Toward a dynamic approach of person perception at zero acquaintance: Applying recurrence quantification analysis to thin slices

Thin-slice methodology has provided us with abundant behavioral streams that self-reported measures would fail to capture, but traditional analytical paradigms in social and personality psychology cannot fully capture the temporal trajectories of person perception at zero acquaintance. At the same time, empirical investigations into how persons and situations jointly predict behavior enacted in situ are scarce, despite the importance of examining real-world behavior to understand any phenomenon of interest. To complement existing theoretical models and analyses, we propose the dynamic latent state-trait model blending dynamical systems theory and person perception. We present a data-driven case study using thin-slice methodology to demonstrate the model. This study provides direct empirical support for the proposed theoretical model on person perception at zero acquaintance highlighting the target, the perceiver, the situation, and time. The results of the study demonstrate that dynamical systems theory approaches can be leveraged to provide information about person perception at zero acquaintance above and beyond that of more traditional approaches. Classification code: 3040 (Social Perception & Cognition)