Modeling Visualization as an Affective Trigger for Human Decision-Making The VP-RAFIAH Framework

Abstract

Visualizations support decision-making, but the steps between seeing a chart and acting on it remain opaque. No formal model captures how seeing moves through emotion into decision quality, so there’s no way to measure it or design against it. VP-RAFIAH (Visual Perceptual Response-Affect Framework for Integrated Affect and Human Decision-Making) addresses this gap by modeling how a visual perceptual response (VPR) generates an affective state, how that state interacts dynamically with ongoing perceptual processing, and how this bidirectional relationship ultimately determines decision quality. Situated in the visualization domain, the framework integrates Ekman’s basic emotion taxonomy with Russell’s valence-arousal circumplex. It frames the full perceptual-affective decision pipeline around three modulating variables: Task, Scenario Context, and Actor.