What distinguishes emotion-label words from emotion-laden words? The characterization of affective meaning from a multi-componential conception of emotions

被引:3
作者
Betancourt, angel-Armando [1 ,2 ]
Guasch, Marc [1 ,2 ]
Ferre, Pilar [1 ,2 ]
机构
[1] Univ Rovira i Virgili, Dept Psicol, Tarragona, Spain
[2] Univ Rovira i Virgili, CRAMC, Tarragona, Spain
关键词
emotion-label words; emotion-laden words; component process model; random forest; valence; feeling; interoception; LEXICAL DECISION; AFFECTIVE NORMS; NEGATIVE WORDS; CORE AFFECT; VALENCE; AROUSAL; ADAPTATION; ANEW; ERP;
D O I
10.3389/fpsyg.2024.1308421
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
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.
引用
收藏
页数:12
相关论文
共 74 条
[11]   Neural correlates of written emotion word processing: A review of recent electrophysiological and hemodynamic neuroimaging studies [J].
Citron, Francesca M. M. .
BRAIN AND LANGUAGE, 2012, 122 (03) :211-226
[12]   EsPal: One-stop shopping for Spanish word properties [J].
Duchon, Andrew ;
Perea, Manuel ;
Sebastian-Galles, Nuria ;
Marti, Antonia ;
Carreiras, Manuel .
BEHAVIOR RESEARCH METHODS, 2013, 45 (04) :1246-1258
[13]   Automatic vigilance for negative words in lexical decision and naming: Comment on Larsen, Mercer, and Balota (2006) [J].
Estes, Zachary ;
Adelman, James S. .
EMOTION, 2008, 8 (04) :441-444
[14]   What Makes a Word a Good Representative of the Category of "Emotion"? The Role of Feelings and Interoception [J].
Ferre, Pilar ;
Guasch, Marc ;
Stadthagen-gonzalez, Hans ;
Hinojosa, Jose Antonio ;
Fraga, Isabel ;
Marin, Javier ;
Perez-sanchez, Miguel Angel .
EMOTION, 2024, 24 (03) :745-758
[15]   Common, uncommon, and novel applications of random forest in psychological research [J].
Fife, Dustin A. ;
D'Onofrio, Juliana .
BEHAVIOR RESEARCH METHODS, 2023, 55 (05) :2447-2466
[16]   The world of emotions is not two-dimensional [J].
Fontaine, Johnny R. J. ;
Scherer, Klaus R. ;
Roesch, Etienne B. ;
Ellsworth, Phoebe C. .
PSYCHOLOGICAL SCIENCE, 2007, 18 (12) :1050-1057
[17]   Effects of achievement contexts on the meaning structure of emotion words [J].
Gentsch, Kornelia ;
Loderer, Kristina ;
Soriano, Cristina ;
Fontaine, Johnny R. J. ;
Eid, Michael ;
Pekrun, Reinhard ;
Scherer, Klaus R. .
COGNITION & EMOTION, 2018, 32 (02) :379-388
[18]   Mapping Emotion Terms into Affective Space Further Evidence for a Four-Dimensional Structure [J].
Gillioz, Christelle ;
Fontaine, Johnny R. J. ;
Soriano, Cristina ;
Scherer, Klaus R. .
SWISS JOURNAL OF PSYCHOLOGY, 2016, 75 (03) :141-148
[19]   Correlation and variable importance in random forests [J].
Gregorutti, Baptiste ;
Michel, Bertrand ;
Saint-Pierre, Philippe .
STATISTICS AND COMPUTING, 2017, 27 (03) :659-678
[20]  
Haro J., 2012, Testmaker: Aplicacion para crear cuestionarios online