https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:13968 Wed 11 Apr 2018 17:13:31 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:28099 Wed 11 Apr 2018 16:54:08 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:25122 Wed 11 Apr 2018 16:05:40 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:25348 Wed 11 Apr 2018 12:33:47 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:25465 Wed 11 Apr 2018 12:31:34 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:9663 Wed 11 Apr 2018 11:21:24 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:28846 Tue 24 Aug 2021 14:38:39 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18239 Tue 23 Jun 2015 18:43:27 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31995 Tue 03 Sep 2019 17:58:26 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27331 Sat 24 Mar 2018 07:38:36 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27403 Sat 24 Mar 2018 07:34:09 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27404 Sat 24 Mar 2018 07:34:08 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:24907 Sat 24 Mar 2018 07:14:52 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:24701 Sat 24 Mar 2018 07:10:53 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:55790 45 years) 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 March 11, 2020. The tweets were analyzed using big data analytics and computational linguistic analyses. Results: Text analyses revealed that nurses made greater use of hashtags and keywords (both monograms and bigrams) associated with burnout, health issues, and mental health compared to construction workers. The COVID-19 pandemic had a pronounced effect on nurses’ tweets, and this was especially noticeable in younger nurses. Tweets about health and well-being contained more first-person singular pronouns and affect words, and health-related tweets contained more affect words. Sentiment analyses revealed that, overall, nurses had a higher proportion of positive sentiment in their tweets than construction workers. However, this changed markedly during the COVID-19 pandemic. Since early 2020, sentiment switched, and negative sentiment dominated the tweets of nurses. No such crossover was observed in the tweets of construction workers. Conclusions: The social media analysis revealed that younger nurses had language use patterns consistent with someone experiencing the ill effects of burnout and stress. Older construction workers had more negative sentiments than younger workers, who were more focused on communicating about social and recreational activities rather than work matters. More broadly, these findings demonstrate the utility of large data sets enabled by social media to understand the well-being of target populations, especially during times of rapid societal change.]]> Sat 22 Jun 2024 12:53:39 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:40690 Mon 18 Jul 2022 09:56:25 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31322 Mon 16 Apr 2018 14:13:21 AEST ]]>