The online language of work-personal conflict

• Published in: Scientific reports Vol. 13; no. 1; p. 21019
• Main Authors: Liou, Gloria, Mittal, Juhi, Sehgal, Neil K. R., Tay, Louis, Ungar, Lyle, Guntuku, Sharath Chandra
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 29-11-2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/477; 631/477/2811; Humanities and Social Sciences; Humans; Language; multidisciplinary; Science; Science (multidisciplinary); Social Media; Social networks; Surveys and Questionnaires
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-48193-3

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.