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Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
Published on: January 29, 2020
Egosyntonicity and emotion regulation: a probabilistic model of valence dynamics
Eleonora Vitanza1, Chiara Mocenni1, Pietro De Lellis2
1Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, Siena 53100, Italy.
Abstract:
In this paper, we introduce a novel Markovian model that describes the impact of egosyntonicity on emotion dynamics. We focus on the dominant current emotion and describe the time evolution of its valence, modelled as a binary variable, where 0 and 1 correspond to negative and positive valences, respectively. In particular, the one-step transition probabilities will depend on the external events happening in daily life, the attention the individual devotes to such events, and the egosyntonicity, modelled as the agreement between the current valence and the internal mood of the individual. A steady-state analysis shows that, depending on the model parameters, four classes of individuals can be identified. Two classes are somewhat expected, corresponding to individuals spending more (less) time in egosyntonicity experiencing positive valences for longer (shorter) times. Surprisingly, two further classes emerge: the self-deluded individuals, where egosyntonicity is associated to a prevalence of negative valences, and the troubled happy individuals, where egodystonicity is associated to positive valences. These findings are aligned with the literature showing that, even if egosyntonicity typically has a positive impact in the short term, it may not always be beneficial in the long run.
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