A generalizable framework for assessing the role of emotion during choice.

The study of emotion has been plagued by several challenges that have left the field fractionated. To date, there is no dominant method for measuring the nebulous and often ill-defined experience of emotion. Here, we offer a new way forward, one that marries numerically precise measurements of affect with current models of human behavior, to more deeply understand the role of emotion during choice, and in particular, during social decision-making. This tool can be combined with multiple other measures that capture different features and levels of the emotional experience, making it particularly flexible to be used in any number of contexts. By operationalizing the classic circumplex model of affect so that it can deliver fine-grained, continuous measurements as affect evolves overtime, our goal is to provide a generalizable and flexible framework for computing affect to infer emotions so that we can assess their impact on human behavior. (PsycInfo Database Record (c) 2023 APA, all rights reserved).