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

机译:通过人工智能和推特语言研究四分之一危机现象

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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.
机译:四分之一的危机(QLC)是在成年早期发生的发展危机事件(18-30)的流行术语。我们的目标是探讨语言主题与社交媒体上讨论的这种现象有关。我们分析了由英国和美国超过1,400名用户编写的1250万推文,提到了QLC,将其员额与由年龄,性别和活动期间匹配的控制用户匹配的人使用的员额进行比较。 Logistic回归用于揭示用户和QLC的单词,主题和情绪之间的重要关联,控制人口统计数据。发现QLC的用户被发现发布更多关于感觉混合的情绪,感觉卡住,想要改变,职业生命,学校和家庭。他们的语言倾向于重点关注未来。根据早期成人危机理论选择的20个术语,QLC组提到了比对照组更高。本研究的见解可以由临床医生和教练使用,以更好地了解年轻人面临的发展挑战以及如何以社交媒体的语言自然地描绘出这些挑战。

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