Browse by author
Lookup NU author(s): Dr Anurag Sharma, Professor Simon See
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2024 During the COVID-19 pandemic, nations implemented various preventive measures, triggering varying online responses. This study examines cultural influences on public online stances toward these measures and their impacts on COVID-19 cases/deaths. Stance detection analysis was used to analyze 16,428,557 Tweets regarding COVID-19 preventive measures from 95 countries, selected based on Hofstede's cultural dimensions. To ensure the variety of population, countries were chosen based on Twitter data availability and a minimum sample size of 385 tweets, achieving a 95% confidence level with a 5% margin of error. The weighted regression analysis revealed that the relationship between culture and online stances depends on the cultural congruence of each measure. Specifically, power distance positively predicted stances for all measures, while indulgence had a negative effect overall. Effects of other cultural indices varied across measures. Individualism negatively affected face coverings stances. Uncertainty avoidance influenced lockdown and vaccination stances negatively but had a positive effect on social distancing stances. Long-term orientation negatively affected lockdown and social distancing stances but positively influenced quarantine stances. Cultural tightness only negatively affected face coverings and quarantine stances. Online stances toward face coverings mediated the relationship between cultural indices and COVID-19 cases/deaths. As such, public health officials should consider cultural profiles and use culturally congruent communication strategies when implementing preventive measures for future pandemics. Furthermore, leveraging digital tools is vital in navigating and shaping online stances to enhance the effectiveness of these measures.
Author(s): Shan W, Yu Quan JC, Wang Z, Sharma A, Ng AB, See S
Publication type: Article
Publication status: Published
Journal: SSM - Population Health
Year: 2024
Volume: 26
Print publication date: 01/06/2024
Online publication date: 07/05/2024
Acceptance date: 06/05/2024
Date deposited: 28/05/2024
ISSN (electronic): 2352-8273
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.ssmph.2024.101679
DOI: 10.1016/j.ssmph.2024.101679
Data Access Statement: Data will be made available on request.
Altmetrics provided by Altmetric
