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The minute-scale dynamics of online emotions reveal the effects of affect labeling.
Fan, Rui; Varol, Onur; Varamesh, Ali; Barron, Alexander; van de Leemput, Ingrid A; Scheffer, Marten; Bollen, Johan.
Afiliação
  • Fan R; State Key Laboratory of Software Development Environment, Beihang University, Beijing, China. buaafanrui@gmail.com.
  • Varol O; Center for Complex Network Research, Northeastern University, Boston, MA, USA.
  • Varamesh A; Center for Complex Networks and Systems Research, Indiana University, Bloomington, IN, USA.
  • Barron A; Center for Complex Networks and Systems Research, Indiana University, Bloomington, IN, USA.
  • van de Leemput IA; Wageningen University, Wageningen, the Netherlands.
  • Scheffer M; Wageningen University, Wageningen, the Netherlands.
  • Bollen J; Center for Complex Networks and Systems Research, Indiana University, Bloomington, IN, USA. jbollen@indiana.edu.
Nat Hum Behav ; 3(1): 92-100, 2019 01.
Article em En | MEDLINE | ID: mdl-30932057
Putting one's feelings into words (also called affect labeling) can attenuate positive and negative emotions. Here, we track the evolution of specific emotions for 74,487 Twitter users by analysing the emotional content of their tweets before and after they explicitly report experiencing a positive or negative emotion. Our results describe the evolution of emotions and their expression at the temporal resolution of one minute. The expression of positive emotions is preceded by a short, steep increase in positive valence and followed by short decay to normal levels. Negative emotions, however, build up more slowly and are followed by a sharp reversal to previous levels, consistent with previous studies demonstrating the attenuating effects of affect labeling. We estimate that positive and negative emotions last approximately 1.25 and 1.5 h, respectively, from onset to evanescence. A separate analysis for male and female individuals suggests the potential for gender-specific differences in emotional dynamics.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fatores de Tempo / Emoções / Mídias Sociais / Idioma Tipo de estudo: Prognostic_studies Limite: Adult / Female / Humans / Male Idioma: En Revista: Nat Hum Behav Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fatores de Tempo / Emoções / Mídias Sociais / Idioma Tipo de estudo: Prognostic_studies Limite: Adult / Female / Humans / Male Idioma: En Revista: Nat Hum Behav Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China