![Sample our Behavioral Sciences journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/110801/TOC-Subject-Sample-2021-Behavioral-Sciences.jpg"})
Abstract
A full understanding of emotions and emotion characteristics can only be reached when their dynamic nature is taken into account. As such, a primary objective of the present study is to describe and account for variability in temporal profiles of experienced emotional intensity. Participants were asked to make detailed drawings of intensity profiles of recently experienced episodes of anger, sadness, joy and affection. Functional data analysis revealed three features that together accounted for 84% of the total variability: (i) steepness at onset; (ii) skewness; and (iii) the number of peaks. Emotions differed with regard to the first two features, with the rise at onset being steeper for sadness and joy and affection being the most negatively skewed emotion under study. Individual differences regarding each of the three features were found, however, they did not strongly generalise across emotions.
Acknowledgements
The present research was supported by Grant GOA/05/04 from the Research Fund of the University of Leuven.
We would like to thank Stephen Loughnan and the anonymous reviewers for their helpful comments on a previous version of this paper.
Notes
The Dutch words used were blijheid, genegenheid, kwaadheid and verdriet, respectively.
Order 1: Sadness, joy, anger, affection; Order 2: Joy, sadness, affection, anger; Order 3: Anger, affection, sadness, joy; Order 4: Affection, anger, joy, sadness.
In particular, before computing the components, we first subtracted the pointwise mean function from each function and, consequently, we discretised the functions into time series data, making use of 150 equally spaced time intervals (Ramsey & Silverman, 2005). Next, we subjected the 1045 × 150 data matrix to a PCA.
The weighted sum of component profiles is added to the pointwise mean function as the latter was subtracted from each function before computing the components.