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    Inferring the Relationship between Anxiety and Extraversion from Tweets during COVID19 – A Linguistic Analytics Approach


    Gruda, Dritjon and Ojo, Adegboyega (2021) Inferring the Relationship between Anxiety and Extraversion from Tweets during COVID19 – A Linguistic Analytics Approach. In: Proceedings of the 54th Hawaii International Conference on System Sciences, January 2021.

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    Abstract

    We investigate the longitudinal relationship between extraversion and experienced state anxiety in a cohort of Twitter users in New York using a linguistic analytics approach. We find that before COVID-19 was declared a pandemic, highly extraverted individuals experienced lower state anxiety compared to more introverted individuals. This is in line with previous literature. However, there seem to be no significant differences between individuals after the pandemic announcement, which provides evidence that COVID19 is affecting individuals regardless of their extraversion trait disposition. Finally, a longitudinal examination of the present 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. Throughout the crisis, state anxiety did not seem to vary much between individuals with different extraversion dispositions.

    Item Type: Conference or Workshop Item (Paper)
    Keywords: Inferring; Relationship; Anxiety; Extraversion; Tweets; COVID-19; Linguistic Analytics Approach;
    Academic Unit: Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI
    Faculty of Social Sciences > School of Business
    Item ID: 15783
    Identification Number: https://doi.org/10.24251/HICSS.2021.328
    Depositing User: Adegboyega Ojo
    Date Deposited: 06 Apr 2022 09:05
    Refereed: Yes
    URI:
      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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