Continuous Time Elicitation Through Virtual Reality to Model Affect Dynamics

Affective states are constantly evolving, ranging from serenity to excitement. Understanding the dynamic transitions between emotional states, known as affect dynamics, is crucial for understanding intraindividual emotional heterogeneity. Various statistical methods have been used to capture and quantify these dynamics, based on longitudinal time series models. However, both the statistical models and experimental design, e.g. Experience Sampling Method, lack a controlled manipulation of the transitions between affective states over time. This study aims to fill this knowledge gap using a meticulous experimental scenario design incorporating controlled affective transitions. For this reason, the study employs Virtual Reality technology to effectively elicit and regulate affective transitions, mimicking real-life situations while offering experimental control. Finally, we proposed an application of the Markovian chain model to analyze affective transition. The study aims to establish a connection between theoretical insights and empirical investigation, providing new avenues for understanding emotional fluctuations within a controlled experimental framework.