The Affective Ising Model: A nonlinear model of affect dynamics
Computational models are often used to formalize and study fluctuations of affect over time. A central question to the creation of such models is which characteristics a computational model should possess in order to adequately describe affect dynamics. In this regard, evidence for the presence of nonlinearity in affect dynamics accumulates. However, it is not yet clear where this nonlinearity comes from: It might either represent an inherent characteristic of affect or it might be an artefact due to environmental effects. In this talk, I will present the Affective Ising Model (AIM) – a nonlinear model of affect dynamics – and detail several studies in which we compared its viability against linear competitor models. By accounting for external events in these studies, we were able to investigate whether the observed nonlinearity in affect is indeed due to external events, or due to affect being nonlinear in nature. Results from each study indicate that the AIM outperforms its competitors, even when accounting for external events. This suggests that nonlinearity is a defining feature of affect and should, consequently, be accounted for in our analyses. Submitted for the symposium “Computational models in affective science” with Kenny Yu, Alan Voodla, Lei Zhang, and Niels Vanhasbroeck.