Emotional Prototypicality Ratings for 636 Chinese Words: A Database of Chinese Words with Affective Information.

Arousal Emotion words Emotionality Prototypicality Valence

Journal

Journal of psycholinguistic research
ISSN: 1573-6555
Titre abrégé: J Psycholinguist Res
Pays: United States
ID NLM: 0333506

Informations de publication

Date de publication:
Dec 2023
Historique:
accepted: 06 09 2023
pubmed: 23 9 2023
medline: 23 9 2023
entrez: 22 9 2023
Statut: ppublish

Résumé

Exemplars of concepts vary in their degree of prototypicality. This is also true for emotion concepts. This study presents prototypicality ratings for a large set of Chinese words. The database contains 636 potential Chinese emotion words (i.e., words that directly express particular emotions, like " happy" and " sad"), from different grammatical categories. Native Chinese speakers rated the words in terms of emotional prototypicality. The database also contains values for valence, arousal, and emotionality. The analyses of the ratings revealed that 502 out of 636 words had a high prototypicality value (value equal to or above three on a 1-to-5 scale), the most prototypical words being negative and high-arousal words. The analyses also indicated that the emotional prototypicality of a word was positively related to both arousal and emotionality, and negatively related to valence. Among these variables, arousal was the most important contributor. Similar results have been found in studies conducted in other languages. This will be a useful resource for researchers interested in studying emotion words in the Chinese language and for those interested in cross-linguistic comparisons.

Identifiants

pubmed: 37740090
doi: 10.1007/s10936-023-10018-9
pii: 10.1007/s10936-023-10018-9
pmc: PMC10703967
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2775-2792

Subventions

Organisme : Spanish Ministry of Science and Innovation
ID : PID2019-107206GB-I00 /AEI/10.13039/501100011033

Informations de copyright

© 2023. The Author(s).

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Auteurs

Ruiyao Zheng (R)

Department of Psychology and CRAMC, Universitat Rovira i Virgili, Carretera de Valls, s.n., 43007, Tarragona, Spain.

Meng Zhang (M)

School of English Studies, Sichuan International Studies University, Chongqing, China.

Taomei Guo (T)

State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.

Marc Guasch (M)

Department of Psychology and CRAMC, Universitat Rovira i Virgili, Carretera de Valls, s.n., 43007, Tarragona, Spain.

Pilar Ferré (P)

Department of Psychology and CRAMC, Universitat Rovira i Virgili, Carretera de Valls, s.n., 43007, Tarragona, Spain. mariadelpilar.ferre@urv.cat.

Classifications MeSH