ArticleInternational journal of environmental research and public health2022
Public Discourse Surrounding Suicide during the COVID-19 Pandemic: An Unsupervised Machine Learning Analysis of Twitter Posts over a One-Year Period.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Exploring the association between social support and anxiety during major public emergencies: a meta-analysis of the COVID-19 pandemic.Frontiers in public health · 2024Pooled it
- Artificial Intelligence in Psychiatry: A Review of Biological and Behavioral Data Analyses.Diagnostics (Basel, Switzerland) · 2025Review
- Understanding Loneliness in Older Adults During the Pandemic: Predictors and Questionnaire Validation.Diseases (Basel, Switzerland) · 2025Article
- Measuring Psychological Strains: A Psychometric Study to Develop a Shortened Version of the Psychological Strain Scales.Behavioral sciences (Basel, Switzerland) · 2024Article
- Article
- Effects of the COVID-19 Pandemic on Depressive Symptoms, Including Clinical and Subthreshold Levels, and Eating Behaviors in First-Year University Students.Complex psychiatryArticle
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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