The semantic structure of emotion words across languages is consistent with componential appraisal models of emotion

ABSTRACT

Appraisal theories of emotion, and particularly the Component Process Model, claim that the different components of the emotion process (action tendencies, physiological reactions, expressions, and feeling experiences) are essentially driven by the results of cognitive appraisals and that the feeling component constitutes a central integration and representation of these processes. Given the complexity of the proposed architecture, comprehensive experimental tests of these predictions are difficult to perform and to date are lacking. Encouraged by the “lexical sedimentation” hypothesis, here we propose an indirect examination of the compatibility of the theoretical assumptions with the semantic structure of a set of major emotion words as measured in a cross-language and cross-cultural study. Specifically, we performed a secondary analysis of the large-scale data set with ratings of affective features covering all components of the emotion process for 24 emotion words in 27 countries, constituting profiles of emotion-specific appraisals, action tendencies, physiological reactions, expressions, and feeling experiences. The results of a series of hierarchical regression analyses to examine the prediction of the theoretical model are highly consistent with the claim that appraisal patterns determine the structure of the response components, which in turn predict central dimensions of the feeling component.

KEYWORDS:

• Emotion process
• appraisal theory
• emotion words
• semantic structure
• lexical sedimentation

Acknowledgement

The authors acknowledge the major contribution of Cristina Soriano in the context of the large-scale international GRID study and helpful comments on this manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by funds granted to K. R. Scherer by the Swiss National Science Foundation [under grant number 100014-122491] and by the FP7 Ideas: European Research Council (ERC) [under Advanced grant number PROPEREMO 230331].