Gruda, Dritjon and Ojo, Adegboyega (2022) All about that trait: Examining extraversion and state anxiety during the SARS-CoV-2 pandemic using a machine learning approach. Personality and Individual Differences, 188. p. 111461. ISSN 0191-8869

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Abstract

We examine the longitudinal relation between extraversion and state anxiety in a large cohort of New York City (NYC) residents using a linguistic analytical machine learning approach. Anxiety, both state and trait, and Big Five personality traits were predicted using micro-blog data on the Twitter platform. In total, we examined 1336 individuals and a total of 200,289 observations across 246 days. We find that before the onset of SARS-CoV-2 in NYC (before 1st March 2020), extraverts experienced lower state anxiety compared to introverted individuals, while this difference shrinks after the onset of the pandemic, which provides evidence that SARS-COV-2 is affecting all individuals regardless of their extraversion trait disposition. Secondly, a longitudinal examination of the presented data shows that extraversion seems to matter more greatly in the early days of the crisis and towards the end of our examined time range. We interpret results within the unique SARS-CoV-2 context and discuss the relationship between SARS-COV-2 and individual differences, namely personality traits. Finally, we discuss results and outline the limitations of our approach.

Item Type:	Article
Keywords:	Anxiety; Extraversion; COVID-19; Longitudinal; Machine learning;
Academic Unit:	Faculty of Social Sciences > School of Business
Item ID:	17629
Identification Number:	https://doi.org/10.1016/j.paid.2021.111461
Depositing User:	Jon Gruda
Date Deposited:	02 Oct 2023 15:18
Journal or Publication Title:	Personality and Individual Differences
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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