Recognition of Emotion from Verbal and Nonverbal Expressions and Its Relation to Effective Communication: A Preliminary Evidence of a Positive Link.

effective communication emotion recognition emotional accuracy empathy language style matching

Journal

Journal of Intelligence
ISSN: 2079-3200
Titre abrégé: J Intell
Pays: Switzerland
ID NLM: 101635592

Informations de publication

Date de publication:
28 Dec 2022
Historique:
received: 20 11 2022
revised: 14 12 2022
accepted: 18 12 2022
entrez: 20 1 2023
pubmed: 21 1 2023
medline: 21 1 2023
Statut: epublish

Résumé

Previous work has shown that emotion recognition is positively related to effective social interactions, but the mechanism underlying this relationship has remained largely unclear. Here, we examined the possibility that people who understand others' emotions also talk to them using similar language. In the current study participants (N = 106) listened to emotional stories people shared from their own lives. They were later asked to recognize the storytellers' feelings and finally provide written support messages. Perceivers' ability to accurately recognize others' feelings was assessed using the Emotional Accuracy Test (EAT), which uses naturalistic verbal and nonverbal emotional cues, and using two standard tests of nonverbal emotion recognition (GERT, RMET). The language of the expressor (target) was compared to the language of the supporter (participant) to quantify Language Style Matching, a proxy for effective communication. People who perform better in emotion recognition with verbal cues (EAT) also communicate their understanding and support using language similar to the expresser (

Identifiants

pubmed: 36662136
pii: jintelligence11010006
doi: 10.3390/jintelligence11010006
pmc: PMC9862275
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Jacob Israelashvili (J)

Psychology Department, The Hebrew University of Jerusalem, Jerusalem 91905, Israel.

Agneta Fischer (A)

Department of Psychology, Social Psychology, University of Amsterdam, Nieuwe Achtergracht 129, 1018 WS Amsterdam, The Netherlands.

Classifications MeSH