What distinguishes emotion-label words from emotion-laden words? The characterization of affective meaning from a multi-componential conception of emotions
- PMID: 38323162
- PMCID: PMC10844498
- DOI: 10.3389/fpsyg.2024.1308421
What distinguishes emotion-label words from emotion-laden words? The characterization of affective meaning from a multi-componential conception of emotions
Abstract
Past research that distinguishes between affective and neutral words has predominantly relied on two-dimensional models of emotion focused on valence and arousal. However, these two dimensions cannot differentiate between emotion-label words (e.g., fear) and emotion-laden words (e.g., death). In the current study, we aimed to determine the unique affective characteristics that differentiate emotion-label, emotion-laden, and neutral words. Therefore, apart from valence and arousal, we considered different affective features of multi-componential models of emotion: action, assessment, expression, feeling, and interoception. The study materials included 800 Spanish words (104 emotion-label words, 340 emotion-laden words, and 356 neutral words). To examine the differences between each word type, we carried out a Principal Component Analysis and a Random Forest Classifier technique. Our results indicate that these words are characterized more precisely when the two-dimensional approach is combined with multi-componential models. Specifically, our analyses revealed that feeling, interoception and valence are key features in accurately differentiating between emotion-label, emotion-laden, and neutral words.
Keywords: component process model; emotion-label words; emotion-laden words; feeling; interoception; random forest; valence.
Copyright © 2024 Betancourt, Guasch and Ferré.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
Figures
References
-
- Addinsoft (2023). XLSTAT statistical and data analysis solution. New York, USA. Available at: https://www.xlstat.com/en
-
- Altarriba J., Basnight-Brown D. M. (2011). The representation of emotion vs. emotion-laden words in English and Spanish in the affective Simon task. Int. J. Biling. 15, 310–328. doi: 10.1177/1367006910379261 - DOI
-
- Archer K. J., Kimes R. V. (2008). Empirical characterization of random forest variable importance measures. Comput. Statistic. Data Analysis 52, 2249–2260. doi: 10.1016/j.csda.2007.08.015 - DOI
-
- Betancourt Á. A., Guasch M., Ferré P. (2023). The contribution of affective content to cue-response correspondence in a word association task: focus on emotion words and emotion-laden words. Appl. Psycholinguist. 44, 991–1011. doi: 10.1017/S0142716423000395 - DOI
LinkOut - more resources
Full Text Sources
Miscellaneous
