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Public Discourse Surrounding Suicide during the COVID-19 Pandemic: An Unsupervised Machine Learning Analysis of Twitter Posts over a One-Year Period

Author

Listed:
  • Shu Rong Lim

    (Health Services Research Unit, Singapore General Hospital, Singapore 169608, Singapore)

  • Qin Xiang Ng

    (Health Services Research Unit, Singapore General Hospital, Singapore 169608, Singapore
    MOH Holdings Pte Ltd., 1 Maritime Square, Singapore 099253, Singapore)

  • Xiaohui Xin

    (Health Services Research Unit, Singapore General Hospital, Singapore 169608, Singapore)

  • Yu Liang Lim

    (MOH Holdings Pte Ltd., 1 Maritime Square, Singapore 099253, Singapore)

  • Evelyn Swee Kim Boon

    (Department of Psychology, Singapore General Hospital, Singapore 169608, Singapore)

  • Tau Ming Liew

    (Department of Psychiatry, Singapore General Hospital, Singapore 169608, Singapore
    SingHealth Duke-NUS Medicine Academic Clinical Programme, Duke-NUS Medical School, Singapore 169857, Singapore
    Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549, Singapore)

Abstract

Many studies have forewarned the profound emotional and psychosocial impact of the protracted COVID-19 pandemic. This study thus aimed to examine how individuals relate to suicide amid the COVID-19 pandemic from a global perspective via the public Twitter discourse around suicide and COVID-19. Original Twitter tweets from 1 February 2020 to 10 February 2021 were searched, with terms related to “COVID-19”, “suicide”, or “self-harm”. An unsupervised machine learning approach and topic modelling were used to identify topics from unique tweets, with each topic further grouped into themes using manually conducted thematic analysis by the study investigators. A total of 35,904 tweets related to suicide and COVID-19 were processed into 42 topics and six themes. The main themes were: (1) mixed reactions to COVID-19 public health policies and their presumed impact on suicide; (2) biopsychosocial impact of COVID-19 pandemic on suicide and self-harm; (3) comparing mortality rates of COVID-19, suicide, and other leading causes of death; (4) mental health support for individuals at risk of suicide; (5) reported cases and public reactions to news related to COVID-19, suicide, and homicide; and (6) figurative usage of the word suicide. The general public was generally concerned about governments’ responses as well as the perturbing effects on mental health, suicide, the economy, and at-risk populations.

Suggested Citation

  • Shu Rong Lim & Qin Xiang Ng & Xiaohui Xin & Yu Liang Lim & Evelyn Swee Kim Boon & Tau Ming Liew, 2022. "Public Discourse Surrounding Suicide during the COVID-19 Pandemic: An Unsupervised Machine Learning Analysis of Twitter Posts over a One-Year Period," IJERPH, MDPI, vol. 19(21), pages 1-15, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:21:p:13834-:d:951912
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    References listed on IDEAS

    as
    1. Takanao Tanaka & Shohei Okamoto, 2021. "Increase in suicide following an initial decline during the COVID-19 pandemic in Japan," Nature Human Behaviour, Nature, vol. 5(2), pages 229-238, February.
    2. Ashraf, Badar Nadeem, 2020. "Economic impact of government interventions during the COVID-19 pandemic: International evidence from financial markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
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