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The online language of work-personal conflict.
Liou, Gloria; Mittal, Juhi; Sehgal, Neil K R; Tay, Louis; Ungar, Lyle; Guntuku, Sharath Chandra.
Afiliação
  • Liou G; Purdue University, West Lafayette, USA. gloriarliou@gmail.com.
  • Mittal J; Rose-Hulman Institute of Technology, Terre Haute, USA. gloriarliou@gmail.com.
  • Sehgal NKR; University of Pennsylvania, Philadelphia, USA.
  • Tay L; University of Pennsylvania, Philadelphia, USA.
  • Ungar L; Purdue University, West Lafayette, USA.
  • Guntuku SC; University of Pennsylvania, Philadelphia, USA.
Sci Rep ; 13(1): 21019, 2023 11 29.
Article em En | MEDLINE | ID: mdl-38030792
ABSTRACT
With the blurring of boundaries in this digital age, there is increasing concern around work-personal conflict. Assessing and tracking work-personal conflict is critical as it not only affects individual workers but is also a vital measure among broader well-being and economic indices. This inductive study examines the extent to which work-personal conflict corresponds to individuals' language use on social media. We apply an open-vocabulary analysis to the posts of 2810 Facebook users who also completed a survey for an established work-personal conflict scale. It was found that the language-based model can predict personal-to-work conflict (r = 0.23) and work-to-personal conflict (r = 0.15) and provide important insights into such conflicts. Specifically, we found that high personal-to-work conflict was associated with netspeak and swearing, while low personal-to-work conflict was associated with language about work and positivity. We found that high work-to-personal conflict was associated with negative emotion and negative tone, while low work-to-personal conflict was associated with positive emotion and language about birthdays.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mídias Sociais / Idioma Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mídias Sociais / Idioma Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article