A model for reappraisal with personality in emotion regulation

ABSTRACT In this paper, an algorithm model is proposed to describe the emotion regulation process of human beings based on Hidden Markov Model (HMM). The process of reappraisal strategy in emotion regulation is optimized by an individual’s personality and the effect of interaction between emotions. Firstly, the theoretical bases in this paper, the theory of Gross emotion regulation process and the Five-Factor Model are described and the relationship between psychology and mathematics models is built by analysing Gross emotion regulation process and HMM. The interaction between emotions affects the initial matrix values by emotional state transition probability. Afterwards, how significantly the personality effects work on reappraisal strategies is elaborated and how to quantify them is discussed. The transition probability matrix based on emotional states is changed with the positions of external emotional stimuli in emotional space and the personality factors of individuals. The simulation results show that the model is effective. The results show that the algorithm can improve the emotion generation and expression in the field of emotion computing in human–computer interaction process and realize the real machine autonomous emotion calculation.

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