Coping with COVID-19

Twitter Content Analysis of Global Mental Health

Stephanie Miodus, M.A., M.Ed., Audris Jimenez, M.A., Stephanie Joseph, M.A., M.Ed., & Nicholas Galea, M.Ed.

Abstract

The COVID-19 pandemic is an unprecedented time thought to have a large impact on mental health. Given the ever-developing nature of the pandemic, there are likely new emerging global mental health needs in response to the financial impact, social isolation, health concerns, and other consequences of COVID-19. However, there is a lack of current literature on the global mental health needs in light of the pandemic. This study seeks to fill the gap by analyzing international Twitter data on the COVID-19 pandemic.

Background

  • Existing literature on COVID-19 and mental health has only emerged from a few affected countries and is not representative of persons living in other parts of the world (Rajkumar, 2020).

  • Symptoms of anxiety and depression as well as self-reported stress are common psychological reactions to the COVID-19 pandemic (Rajkumar, 2020).

  • Some groups are more vulnerable than others to the psychosocial effects of pandemics (Pfefferbaum & North, 2020).

  • In the past decade, there has been a rise in social media and information sharing systems allowing researchers to analyze online textual data in real time. Social media provides researchers a snapshot of the public’s opinions and behavioral responses (Chew & Eysenbach, 2009).

  • Surveys are time consuming especially during a time of immediate need (i.e., pandemics; Chew & Eysenbach, 2009).

  • Social media provides an avenue to measure mental health trends across multiple communities (Guntuku et al., 2020).

  • Previous pandemic twitter studies saw an increase in World Health Organization terminology through the duration of the pandemic (Chew & Eysenbach, 2009).

Present Study

Exploratory analysis to examine the changes in global mental health trends over time during the COVID-19 pandemic.

Methodology

  • Data collected from publicly available Tweets

  • Tweets included in analysis included mention of COVID-19, coronavirus, pandemic, etc.

  • Examined results on a biweekly basis to track changes over time during the pandemic

  • Randomly selected two hours per analyzed day

  • 2,715,856 Tweets included in current analysis

  • Analysis included global Tweets that were in English

  • Content analysis performed on Tweets based on predetermined terms categorized as anxiety, depression, positivity, and stress content

    • Search criteria found here

Results

  • Anxiety content has decreased over time since it peaked in March and April.

  • Anxiety, depression, positivity, and stress content have remained relatively stable in recent weeks.

Discussion

  • With almost 3 million global tweets utilized in the current study, these near real-time results can provide mental health professionals and policy makers with vital data on how to allocate their resources to better respond to public concerns.

  • While mention of anxiety has decreased, stress has remained constant and may be an area of mental health need during the pandemic. Policymakers should explore allocating funds to address stress during the pandemic.

  • Data collection from social media opens up the sample pool to broader global demographics.

Limitations & Future Directions

  • Data collection procedures did not account for daily changes that could occur or control for day of the week.

        • For future studies, the data can be collected on different days of the week or daily.

  • Only public tweets were utilized; private tweets were not accessible, which limits the data collected.

  • The data utilized is only from people that use Twitter.

        • Future studies could be conducted utilizing other social media services like Instagram. The rise in social media requires a shift in data collection techniques, as 72% of the public utilize some type of social media (Pew Research Center, 2019).

References

Chen, E., Lerman, K., & Ferrara, E. (2020). Tracking social media discourse about the covid-19 pandemic: Development of a public coronavirus twitter data set. JMIR Public Health and Surveillance, 6(2), e19273. https://doi.org/10.2196/19273

Chew, C., & Eysenbach, G. (2010). Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak. PloS one, 5(11), e14118. https://doi.org/10.1371/journal.pone.0014118

Guntuku, S.C., Sherman, G., Stokes, D.C. et al. Tracking Mental Health and Symptom Mentions on Twitter During COVID-19. J GEN INTERN MED 35, 2798–2800 (2020). https://doi.org/10.1007/s11606-020-05988-8

Pew Research Center. (2019, June 12). Social Media Fact Sheet. https://www.pewresearch.org/internet/fact-sheet/social-media/

Pfefferbaum, B., & North, C. S. (2020). Mental health and the Covid-19 pandemic. New England Journal of Medicine, 383(6), 510-512. https://doi.org/10.1056/NEJMp2008017

Rajkumar R. P. (2020). COVID-19 and mental health: A review of the existing literature. Asian Journal of Psychiatry, 52, 102066. https://doi.org/10.1016/j.ajp.2020.102066