371
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Stories or Directives: A Cross Cultural Comparison of Governmental Messages to Their Constituents during COVID-19

, &

References

  • Al-Alawi, A., & Alkhodari, H. J. (2016). Cross-cultural differences in managing businesses: Applying Hofstede cultural analysis in Germany, Canada, South Korea and Morocco. Elixir International Business Management, 95, 40855–40861. https://www.elixirpublishers.com/articles/1465542455_95%20(2016)%2040855-40861.pdf
  • Bilandzic, H., & Busselle, R. W. (2013). Narrative persuasion. In J. P. Dillard & L. Shen (Eds.), The Sage handbook of persuasion: Developments in theory and practice (pp. 200–219). Sage.
  • Borgida, E., & Nisbett, R. E. (1977). The differential impact of abstract vs. concrete information on decisions. Journal of Applied Social Psychology, 7(3), 258–271. https://doi.org/10.1111/j.1559-1816.1977.tb00750.x
  • Braddock, K., & Dillard, J. P. (2016). Meta-analytic evidence for the persuasive effect of narratives on beliefs, attitudes, intentions, and behaviors. Communication Monographs, 83(4), 446–467. https://doi.org/10.1080/03637751.2015.1128555
  • Brehm, J. W. (1966). A theory of psychological reactance. Academic Press.
  • Centers for Disease Control and Prevention. (2021, July 28). COVID data tracker. https://covid.cdc.gov/covid-data-tracker/#cases_totalcases
  • Centers for Disease Control and Prevention [ @CDCgov]. (n.d.). Tweets [ Twitter Profile]. Retrieved July 28, 2021, from https://twitter.com/CDCgov
  • Chen, Q., Min, C., Zhang, W., Wang, G., Ma, X., & Evans, R. (2020). Unpacking the black box: How to promote citizen engagement through government social media during the COVID-19 crisis. Computers in Human Behavior, 110, 106380. https://doi.org/10.1016/j.chb.2020.106380
  • Demirbas, M., Ali Bayir, M., Akcora, C. G., Yilmaz, Y. S., & Ferhatosmanoglu, H. (2010, November). Crowd-sourced sensing and collaboration using Twitter. In IEEE international symposium on “A World of Wireless, Mobile and Multimedia Networks” (pp. 1–9). IEEE. https://doi.org/10.1109/WOWMOM.2010.5534910
  • Dillard, J. P. (1998). Evaluating and using meta-analyses. In M. Allen & R. Preiss (Eds.), Persuasion: Advances through meta-analysis (pp. 257–270). Hampton Press.
  • Eugster, P. T., Felber, P. A., Guerraoui, R., & Kermarrec, A. M. (2003). The many faces of publish/subscribe. ACM Computing Surveys, 35(2), 114–131. https://doi.org/10.1145/857076.857078
  • Fisher, W. R. (1984). Narration as a human communication paradigm: The case of public moral argument. Communication Monographs, 51(1), 1–22. https://doi.org/10.1080/03637758409390180
  • Fung, I. C., Duke, C. H., Finch, K. C., Snook, K. R., Tseng, P. L., Hernandez, A. C., Gambhir, M., Fu, K. W., & Tse, Z. T. (2016). Ebola virus disease and social media: A systematic review. American Journal of Infection Control, 44(12), 1660–1671. https://doi.org/10.1016/j.ajic.2016.05.011
  • Fung, I. C., Fu, K. W., Ying, Y., Schaible, B., Hao, Y., Chan, C. H., & Tse, Z. T. (2013). Chinese social media reaction to the MERS-CoV and avian influenza A(H7N9) outbreaks. Infectious Diseases of Poverty, 2(1), 31. https://doi.org/10.1186/2049-9957-2-31
  • Fung, I. C., Zeng, J., Chan, C. H., Liang, H., Yin, J., Liu, Z., Tse, Z. T., & Fu, K. W. (2017). Twitter and Middle East respiratory syndrome, South Korea, 2015: A multi-lingual study. Infection, Disease & Health, 23(1), 10–16. https://doi.org/10.1016/j.idh.2017.08.005
  • Gao, Q., Abel, F., Houben, G. J., & Yu, Y. (2012). A comparative study of users’ microblogging behavior on Sina Weibo and Twitter. In J. Masthoff, B. Mobasher, M. C. Desmarais, & R. Nkambou (Eds.), User modeling, adaptation, and personalization (pp. 88–101). Springer. https://doi.org/10.1007/978-3-642-31454-4_8
  • Hall, E. T. (1976). Beyond culture. Anchor Press.
  • Hargittai, E., & Litt, E. (2011). The tweet smell of celebrity success: Explaining variation in Twitter adoption among a diverse group of young adults. New Media & Society, 13(5), 824–842. https://doi.org/10.1177/1461444811405805
  • Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and organizations: Software of the mind (3rd ed.). McGraw-Hill.
  • Hofstede, G. (1980). Culture’s consequences: International differences in work-related values. Sage.
  • Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations (2nd ed.). Sage.
  • Jernigan, D. B. (2020). Update: Public health response to the coronavirus disease 2019 outbreak — United States, February 24, 2020. Morbidity and Mortality Weekly Report, 69(8), 216–219. https://doi.org/10.15585/mmwr.mm6908e1
  • Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80(4), 237–251. https://doi.org/10.1037/h0034747
  • Kearney, M. (2019). Rtweet: Collecting and analyzing twitter data. Journal of Open Source Software, 4(42), 1829. https://doi.org/10.21105/joss.01829
  • Lai, C. C., Shih, T. P., Ko, W. C., Tang, H. J., & Hsueh, P. R. (2020). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges. International Journal of Antimicrobial Agents, 55(3), 105924. https://doi.org/10.1016/j.ijantimicag.2020.105924
  • Lau, H., Khosrawipour, V., Kocbach, P., Mikolajczyk, A., Schubert, J., Bania, J., & Khosrawipour, T. (2020). The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China. Journal of Travel Medicine, 27(3), taaa037. https://doi.org/10.1093/jtm/taaa037
  • Lazard, A. J., Scheinfeld, E., Bernhardt, J. M., Wilcox, G. B., & Suran, M. (2015). Detecting themes of public concern: A text mining analysis of the Centers for Disease Control and Prevention’s Ebola live Twitter chat. American Journal of Infection Control, 43(10), 1109–1111. https://doi.org/10.1016/j.ajic.2015.05.025
  • Li, C., & Wu, D. D. (2018). Facework by global brands across Twitter and Weibo. Discourse, Context & Media, 26, 32–42. https://doi.org/10.1016/j.dcm.2018.03.006
  • Li, S., Wang, Y., Xue, J., Zhao, N., & Zhu, T. (2020). The impact of COVID-19 epidemic declaration on psychological consequences: A study on active Weibo users. International Journal of Environmental Research and Public Health, 17(6), 2032. https://doi.org/10.3390/ijerph17062032
  • Liao, Q., Yuan, J., Dong, M., Yang, L., Fielding, R., & Lam, W. W. T. (2020). Public engagement and government responsiveness in the communications about COVID-19 during the early epidemic stage in China: Infodemiology study on social media data. Journal of Medical Internet Research, 22(5), e18796. https://doi.org/10.2196/18796
  • Liu, K., Li, L., Jiang, T., Chen, B., Jiang, Z., Wang, Z., Chen, Y., Jiang, J., & Gu, H. (2016). Chinese public attention to the outbreak of Ebola in West Africa: Evidence from the online big data platform. International Journal of Environmental Research and Public Health, 13(8), 780. https://doi.org/10.3390/ijerph13080780
  • Lu, H., Stratton, C. W., & Tang, Y. (2020). Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle. Journal of Medical Virology, 92(4), 401–402. https://doi.org/10.1002/jmv.25678
  • Ma, L. (2013). Electronic word-of-mouth on microblogs: A cross-cultural content analysis of Twitter and Weibo. Intercultural Communication Studies, 22(3), 18–42.
  • Motoyama, M., Meeder, B., Levchenko, K., Voelker, G. M., & Savage, S. (2010). Measuring online service availability using Twitter. In Proceedings of the 3rd conference on online social networks (pp. 13). USENIX. https://cseweb.ucsd.edu/~savage/papers/WOSN10.pdf
  • Muccari, R., & Chow, D. (2020, May). Coronavirus timeline: Tracking the critical moments of COVID-19. NBC News. https://www.nbcnews.com/health/health-news/coronavirus-timeline-tracking-critical-moments-covid-19-n1154341
  • National Health Commission of the People’s Republic of China [ @Jiankang Zhongguo (Health China)]. (n.d.). Sina Weibo posts [ Sina Weibo Profile]. Retrieved July 28, 2021, from https://www.weibo.com/jiankangzhongguo?is_hot=1
  • Oschatz, C., & Marker, C. (2020). Long-term persuasive effects in narrative communication research: A meta-analysis. Journal of Communication, 70(4), 473–496. https://doi.org/10.1093/joc/jqaa017
  • Parascandola, J. (1996). From MCWA to CDC – Origins of the Centers for Disease Control and Prevention. Public Health Reports, 111(6), 549–551.
  • Shen, F., Sheer, V. C., & Li, R. (2015). Impact of narratives on persuasion in health communication: A meta-analysis. Journal of Advertising, 44(2), 105–113. https://doi.org/10.1080/00913367.2015.1018467
  • State Council Information Office of the People’s Republic of China. (2020). Fighting COVID-19: China in action. https://covid-19.chinadaily.com.cn/a/202006/08/WS5edd8bd6a3108348172515ec.html
  • Tao, Z. Y., Chu, G., McGrath, C., Hua, F., Leung, Y. Y., Yang, W. F., & Su, Y. X. (2020). Nature and diffusion of covid-19–related oral health information on Chinese social media: Analysis of tweets on Weibo. Journal of Medical Internet Research, 22(6), e19981. https://doi.org/10.2196/19981
  • Taylor, S. E., & Thompson, S. C. (1982). Stalking the elusive “vividness” effect. Psychological Review, 89(2), 155–181. https://doi.org/10.1037/0033-295X.89.2.155
  • Tracy, S. J. (2013). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact. Wiley-Blackwell.
  • Treiber, M., Schall, D., Dustdar, S., & Scherling, C. (2011, May). Tweetflows: Flexible workflows with Twitter. In Proceeding of the 3rd international workshop on principles of engineering service-oriented systems (pp. 1–7). International Conference on Software Engineering (ICSE). https://doi.org/10.1145/1985394.1985395
  • Trupthi, M., Pabboju, S., & Narasimha, G. (2017, October). Sentiment analysis on Twitter using streaming api. In 2017 IEEE 7th international advance computing conference (pp. 915–919). IEEE. https://doi.org/10.1109/IACC.2017.0186
  • World Health Organization. (2020a, January 30). WHO Director-General’s statement on IHR emergency committee on novel coronavirus (2019-nCoV). https://www.who.int/dg/speeches/detail/who-director-general-s-statement-on-ihr-emergency-committee-on-novel-coronavirus-(2019-ncov)
  • World Health Organization. (2020b). Coronavirus disease (COVID-19) situation report (No. 162). https://www.who.int/docs/default-source/coronaviruse/20200630-covid-19-sitrep-162.pdf?sfvrsn=e00a5466_2
  • World Health Organization. (2020c). Coronavirus disease (COVID-19) situation report (No. 203). https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200810-covid-19-sitrep-203.pdf?sfvrsn=aa050308_4
  • Wu, D. D., & Li, C. (2018). Emotional branding on social media: A cross-cultural discourse analysis of global brands on Twitter and Weibo. In A. Curtis & R. Sussex (Eds.), Intercultural communication in Asia: Education, language and values (pp. 225–240). Springer. https://doi.org/10.1007/978-3-319-69995-0_11

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.