Data

A text data set of 1.5M tweets from workers in the construction and nursing industries.

Western Sydney University
Li, Weicong ; Tang, Liyaning (Maggie) ; Montayre, Jed ; Harris, Celia ; West, Sancia ; Antoniou, Mark
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26183/stka-v668&rft.title=Investigating health and wellbeing challenges facing an ageing workforce in the construction and nursing industries: Twitter data set&rft.identifier=10.26183/stka-v668&rft.publisher=Western Sydney University&rft.description=Construction and nursing are critical industries within New South Wales and Australia. Though both careers involve physically and mentally demanding work, the risks to workers during the pandemic are not well understood. In prior work, we have shown that nurses (both younger and older) were more likely to suffer the ill effects of burnout and stress than construction workers. This seems likely linked to accelerated work demands and increased pressure on nurses during the COVID-19 pandemic. Here, we subjected a large social media dataset to a series of advanced natural language processing techniques in order to explore indicators of mental status across industries before and during the COVID-19 pandemic. Objective: This social media analysis fills an important knowledge gap by comparing the social media posts of younger and older construction workers and nurses in order to obtain an insight into any potential risks to their mental health due to work health and safety issues. Methods: We analysed 1,505,638 tweets published on Twitter by younger and older (45 years of age) construction workers and nurses. The study period spanned 54 months, from January 2018 to June 2022, which equates to approximately 27 months before and 27 months after the World Health Organization declared COVID-19 a global pandemic on 11 March 2020. The tweets were analysed using big data analytics and computational linguistic analyses. &rft.creator=Li, Weicong &rft.creator=Tang, Liyaning (Maggie) &rft.creator=Montayre, Jed &rft.creator=Harris, Celia &rft.creator=West, Sancia &rft.creator=Antoniou, Mark &rft.date=2023&rft.relation=https://preprints.jmir.org/preprint/49450&rft.coverage=141.087277,-37.346143 141.087277,-28.895184 154.355217,-28.895184 154.355217,-37.346143 141.087277,-37.346143&rft.coverage=&rft_rights=Copyright Western Sydney University&rft_rights=CC BY 4.0: Attribution 4.0 International http://creativecommons.org/licenses/by/4.0&rft_subject=twitter&rft_subject=nursing&rft_subject=construction&rft_subject=WHS&rft_subject=Nursing&rft_subject=HEALTH SCIENCES&rft_subject=Building organisational studies&rft_subject=Building&rft_subject=BUILT ENVIRONMENT AND DESIGN&rft_subject=Clinical and health psychology&rft_subject=PSYCHOLOGY&rft_subject=Social and personality psychology&rft_subject=Linguistics&rft_subject=LANGUAGE, COMMUNICATION AND CULTURE&rft_subject=Expanding knowledge&rft_subject=EXPANDING KNOWLEDGE&rft_subject=Health related to ageing&rft_subject=Specific population health (excl. Indigenous health)&rft_subject=HEALTH&rft_subject=Occupational health&rft.type=dataset&rft.language=English Access the data

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CC BY 4.0: Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0

Copyright Western Sydney University

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Full description

Construction and nursing are critical industries within New South Wales and Australia. Though both careers involve physically and mentally demanding work, the risks to workers during the pandemic are not well understood. In prior work, we have shown that nurses (both younger and older) were more likely to suffer the ill effects of burnout and stress than construction workers. This seems likely linked to accelerated work demands and increased pressure on nurses during the COVID-19 pandemic. Here, we subjected a large social media dataset to a series of advanced natural language processing techniques in order to explore indicators of mental status across industries before and during the COVID-19 pandemic. Objective: This social media analysis fills an important knowledge gap by comparing the social media posts of younger and older construction workers and nurses in order to obtain an insight into any potential risks to their mental health due to work health and safety issues. Methods: We analysed 1,505,638 tweets published on Twitter by younger and older (<45 vs. >45 years of age) construction workers and nurses. The study period spanned 54 months, from January 2018 to June 2022, which equates to approximately 27 months before and 27 months after the World Health Organization declared COVID-19 a global pandemic on 11 March 2020. The tweets were analysed using big data analytics and computational linguistic analyses.

Created: 2023-11-07

Data time period: 03 2022 to 31 07 2022

This dataset is part of a larger collection

Click to explore relationships graph

141.08728,-37.34614 141.08728,-28.89518 154.35522,-28.89518 154.35522,-37.34614 141.08728,-37.34614

147.721247,-33.1206635

Identifiers
  • DOI : 10.26183/STKA-V668
  • Local : research-data.westernsydney.edu.au/published/da3f70c07d1511eea5c4c9c26f8c077b