Using emotional scripts to generate and validate a set of emotion verbs
- Published
- Accepted
- Subject Areas
- Psychiatry and Psychology
- Keywords
- Emotional scripts, Emotion verbs, Discrete emotions, Language as Context
- Copyright
- © 2015 Portch et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Using emotional scripts to generate and validate a set of emotion verbs. PeerJ PrePrints 3:e903v1 https://doi.org/10.7287/peerj.preprints.903v1
Abstract
Information about everyday emotional experiences is integrated into internal scripts (e.g. Shaver et al., 1987). Script content provides a context within which to compare and subsequently interpret newly experienced, emotional stimuli, such as facial expressions and behaviours. We explore whether this internal context may also be used to interpret emotional words. In particular, we argue that the ‘meaning’ of emotional verbs may be strongly context-dependent (e.g. Schacht & Sommer, 2009). Harnessing previous context-based methods, we define verb meaning by the degree of association between the behaviours to which they refer and discrete emotional states (e.g. ‘fear’), within emotional scripts (Stevenson, Mikels & James, 2007). We used a self-generation method to derive a set of verbs that participants associated with six universal, emotional states (study 1; see full list in appendix A). Emotion labels acted as script anchors. For each verb, degree of emotionality and discrete association were measured by the number of participants who generated that word. As expected, a different modal exemplar was generated for each discrete emotion. In study 2 we used a rating task to assess the stability of the relationship between modal, or typical, verbs and the emotion label to which they had been generated. Verbs and labels were embedded in a sentence and participants were invited to reflect on their emotional attributions in everyday life to rate the association (‘If you are feeling ‘sad’ how likely would you be to act in the following way?’ e.g. ’cry’). Findings suggest that typical relationships were robust. Participants always gave higher ratings to typical vs. atypical verb and label pairings even when (a) rating direction was manipulated (the label or verb appeared first in the sentence), and (b) the typical behaviours were to be performed by themselves or others ( ‘If someone is sad, how likely are they to act in the following way?’ e.g. ’cry’). Our findings suggest that emotion scripts create verb meaning, and therefore provide a context within which to interpret emotional words. We provide a set of emotion verbs that are robustly associated with discrete, emotional labels/states. This resource may be used by a variety of researchers, including those interested in categorical processing of emotional words and language-mediated facial mimicry.
Author Comment
This is a submission to PeerJ for review.