ArticleHealth information science and systems2023
Leveraging twitter data to understand nurses' emotion dynamics during the COVID-19 pandemic.
Article in Health information science and systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A novel adaptive sigma KNN model for depression and anxiety detection following the COVID 19 pandemic.Scientific reports · 2025Article
- Clustering analysis for the evolutionary relationships of SARS-CoV-2 strains.Scientific reports · 2024Article
- The Utilization of Natural Language Processing for Analyzing Social Media Data in Nursing Research: A Scoping Review.Journal of nursing management · 2024Article
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Authors and funding
7 authors.
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Abstract
The nursing workforce is the largest discipline in healthcare and has been at the forefront of the COVID-19 pandemic response since the outbreak of COVID-19. However, the impact of COVID-19 on the nursing workforce is largely unknown as is the emotional burden experienced by nurses throughout the different waves of the pandemic. Conventional approaches often use survey question-based instruments to learn nurses' emotions, and may not reflect actual everyday emotions but the beliefs specific to survey questions. Social media has been increasingly used to express people's thoughts and feelings. This paper uses Twitter data to describe the emotional dynamics of registered nurse and student nurse groups residing in New South Wales in Australia during the COVID-19 pandemic. A novel analysis framework that considered emotions, talking topics, the unfolding development of COVID-19, as well as government public health actions and significant events was utilised to detect the emotion dynamics of nurses and student nurses. The results found that the emotional dynamics of registered and student nurses were significantly correlated with the development of COVID-19 at different waves. Both groups also showed various emotional changes parallel to the scale of pandemic waves and corresponding public health responses. The results have potential applications such as to adjust the psychological and/or physical support extended to the nursing workforce. However, this study has several limitations that will be considered in the future study such as not validated in a healthcare professional group, small sample size, and possible bias in tweets.
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Registered trials
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