Examining the phenomenon of quarter-life crisis through artificial intelligence and the language of Twitter

Agarwal, Shantenu, Guntuku, Sharath Chandra, Robinson, Oliver C, Dunn, Abigail and Ungar, Lyle H (2020) Examining the phenomenon of quarter-life crisis through artificial intelligence and the language of Twitter. Frontiers in Psychology, 11. a341 1-11. ISSN 1664-1078

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Abstract

Quarter-life crisis (QLC) is a popular term for developmental crisis episodes that occur during early adulthood (18–30). Our aim was to explore what linguistic themes are associated with this phenomenon as discussed on social media. We analyzed 1.5 million tweets written by over 1,400 users from the United Kingdom and United States that referred to QLC, comparing their posts to those used by a control set of users who were matched by age, gender and period of activity. Logistic regression was used to uncover significant associations between words, topics, and sentiments of users and QLC, controlling for demographics. Users who refer to a QLC were found to post more about feeling mixed emotions, feeling stuck, wanting change, career, illness, school, and family. Their language tended to be focused on the future. Of 20 terms selected according to early adult crisis theory, 16 were mentioned by the QLC group more than the control group. The insights from this study could be used by clinicians and coaches to better understand the developmental challenges faced by young adults and how these are portrayed naturalistically in the language of social media.

Item Type: Article
Keywords: emerging adulthood, machine learning, natural language processing, quarter-life crisis, social media
Schools and Departments: School of Psychology > Psychology
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 30 Oct 2020 09:28
Last Modified: 30 Oct 2020 09:30
URI: http://sro.sussex.ac.uk/id/eprint/94673

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