Computational modeling of appraisal theory of emotion
Ben Meuleman
Appraisal theories of emotion claim that appraisals are a major determining factor in the unfolding of
emotional episodes, predicting effects of appraisal on physiological responses, motor expression,
motivational tendencies, subjective feeling and verbal labeling of emotion. While numerous studies
have supported these predictions, there is ongoing uncertainty about the precise algorithms that
translate information of appraisal to emotional responses. Theoretical proposals about nonlinear and
time-dependent appraisal processes have been put forward but rarely studied in practice. The aim of
this project is to investigate appraisal mechanisms using models from the field of statistical machine
learning. In this presentation, I briefly review theoretical and practical approaches to appraisal
modeling. In addition, I present results from a large-scale appraisal study where machine learning was
applied. Finally, I list the most important open challenges in modeling the relation between appraisal
and emotion.