Belief and Behaviour of Mauritian Social Media Users with Respect to COVID-19

Mc, Sun; Jeetun, Beneeta; Neerunjun, Deevya; Cheeneebash, Jayrani

doi:10.2139/ssrn.3699783

Cited by 1 publication

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“…The social media analytics results can be used to evaluate hospitals on possible social media messaging strategies and recommend targeted interventions to implement during a pandemic. Based on the findings, JEIM 36,6 we recommend hospitals to at least: (a) employ social media analytics to capture public perceptions and act accordingly, (b) customize their social media messaging based on HBMrelated variables to get the communities they served well prepared for COVID-19 and future pandemics, (c) design health awareness and education programs or campaigns according to age groups, place of residence and education level (Sun et al, 2020) since people have different levels of belief on the four HBM constructs, and d) inform specific health care policies that will improve the health outcomes for people with different demographical characteristics in the communities they serve.…”

Section: Discussionmentioning

confidence: 99%

Using health belief model and social media analytics to develop insights from hospital-generated twitter messaging and community responses on the COVID-19 pandemic

Tian

et al. 2023

JEIM

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PurposeThis study aims to examine how different hospitals utilize social media to communicate risk information about COVID-19 with the communities they serve, and how hospitals' social media messaging (firm-generated content and their local community's responses (user-generated content) evolved with the COVID-19 outbreak progression.Design/methodology/approachThis research proposes a healthcare-specific social media analytics framework and studied 68,136 tweets posted from November 2019 to November 2020 from a geographically diverse set of ten leading hospitals' social media messaging on COVID-19 and the public responses by using social media analytics techniques and the health belief model (HBM).FindingsThe study found correlations between some of the HBM variables and COVID-19 outbreak progression. The findings provide actionable insight for hospitals regarding risk communication, decision making, pandemic awareness and education campaigns and social media messaging strategy during a pandemic and help the public to be more prepared for information seeking in the case of future pandemics.Practical implicationsFor hospitals, the results provide valuable insights for risk communication practitioners and inform the way hospitals or health agencies manage crisis communication during the pandemic For patients and local community members, they are recommended to check out local hospital's social media sites for updates and advice.Originality/valueThe study demonstrates the role of social media analytics and health behavior models, such as the HBM, in identifying important and useful data and knowledge for public health risk communication, emergency responses and planning during a pandemic.

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Section: Discussionmentioning

confidence: 99%

Using health belief model and social media analytics to develop insights from hospital-generated twitter messaging and community responses on the COVID-19 pandemic

Tian

et al. 2023

JEIM

View full text Add to dashboard Cite

show abstract

Belief and Behaviour of Mauritian Social Media Users with Respect to COVID-19

Cited by 1 publication

References 0 publications

Using health belief model and social media analytics to develop insights from hospital-generated twitter messaging and community responses on the COVID-19 pandemic

Using health belief model and social media analytics to develop insights from hospital-generated twitter messaging and community responses on the COVID-19 pandemic

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