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Examining the Phenomenon of Quarter-Life Crisis Through Artificial Intelligence and the Language of Twitter

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...

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Autores principales: Agarwal, Shantenu, Guntuku, Sharath Chandra, Robinson, Oliver C., Dunn, Abigail, Ungar, Lyle H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068850/
https://www.ncbi.nlm.nih.gov/pubmed/32210878
http://dx.doi.org/10.3389/fpsyg.2020.00341
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author Agarwal, Shantenu
Guntuku, Sharath Chandra
Robinson, Oliver C.
Dunn, Abigail
Ungar, Lyle H.
author_facet Agarwal, Shantenu
Guntuku, Sharath Chandra
Robinson, Oliver C.
Dunn, Abigail
Ungar, Lyle H.
author_sort Agarwal, Shantenu
collection PubMed
description 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.
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spelling pubmed-70688502020-03-24 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 Ungar, Lyle H. Front Psychol Psychology 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. Frontiers Media S.A. 2020-03-06 /pmc/articles/PMC7068850/ /pubmed/32210878 http://dx.doi.org/10.3389/fpsyg.2020.00341 Text en Copyright © 2020 Agarwal, Guntuku, Robinson, Dunn and Ungar. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Agarwal, Shantenu
Guntuku, Sharath Chandra
Robinson, Oliver C.
Dunn, Abigail
Ungar, Lyle H.
Examining the Phenomenon of Quarter-Life Crisis Through Artificial Intelligence and the Language of Twitter
title Examining the Phenomenon of Quarter-Life Crisis Through Artificial Intelligence and the Language of Twitter
title_full Examining the Phenomenon of Quarter-Life Crisis Through Artificial Intelligence and the Language of Twitter
title_fullStr Examining the Phenomenon of Quarter-Life Crisis Through Artificial Intelligence and the Language of Twitter
title_full_unstemmed Examining the Phenomenon of Quarter-Life Crisis Through Artificial Intelligence and the Language of Twitter
title_short Examining the Phenomenon of Quarter-Life Crisis Through Artificial Intelligence and the Language of Twitter
title_sort examining the phenomenon of quarter-life crisis through artificial intelligence and the language of twitter
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068850/
https://www.ncbi.nlm.nih.gov/pubmed/32210878
http://dx.doi.org/10.3389/fpsyg.2020.00341
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