Theorizing for COVID 19 Infodemic in Iran Social Media

Document Type : Research Article

Authors

1 Professor, Department of Communicatio studies, University of Allameh Tabataba’i,

2 PhD Graduate in Communicatio studies, University of Allameh Tabataba’i

Abstract

Introduction: COVID 19 Infodemic was the title of a communication phenomenon launched by the Director-General of the World Health Organization to accompany the CORONA virus spreading worldwide. Misinformation circulates quickly on social media, and the fight against fake news will likely continue until the virus outbreak. As a result, the World Health Organization is currently working with social media to disseminate accurate information about COVID 19. This crisis is characterized by the simultaneous spread of the virus and the information itself. In other words, not only the virus itself spread very quickly, but also the misinformation about the spread of the disease, which caused the panic in the population to grow rapidly. In other words, the fear fueled by social media grew even faster than the spread of COVID 19 in the population. So, the main theme of COVID 19 Infodemic is to combat the spread of inaccurate or unnecessary information or so-called “intelligence” at the global, national, and regional levels. The word infodemic is an abbreviation of the two words (info) or the same information and (demi), which has Greek roots and refers to population and people. Infodemics consists of the words information (demi) and demi (Greek root that goes back to people). In addition, demi has its own root in medical debates. “Epi” has Greek roots meaning above and below. Yet, pandemics have Greek origins and “pan” means all, everywhere, or overcoming, which is more effective than an epidemic. An infodemic can be thought of as a large amount of information published in a harmful way in the media. This article aims to discuss the issue of Covid 19 infodemic in the context of health communication and theorize the components, production areas, and ways of dealing with it in Iranian social media.
Methods: The approach used in this article is qualitative and the research method is grounded theory. Therefore, instead of using existing theories as a theoretical framework, the researchers attempted to develop their own grounded theory from the data obtained. For this purpose, the theoretical sampling method and expert interviews were used to collect the necessary data from various sources. After this step, all data were coded using open, axial, and selective coding instructions.
Findings: Eventually, 74 concepts and 28 categories were extracted from the data and COVID 19 Infodemic in social media was identified as a central phenomenon. Using a paradigmatic model, the grounded theory derived from the data is presented in the form of a narrative and visual model.
Conclusions: Key findings of this study include the public’s diminishing trust in official institutions and the media, the politicization of health, and elite infodemics, all of which have contributed in some way to the emergence and spread of infodemics. The lack of an epidemiological perspective and the duality of care-cue and quantitative-qualitative approaches were also identified as the most prominent factors. Telos and inductive factors, inefficiency of management, weakness of civil institutions, censorship and filtering, and celebrity intervention are the main confounding factors in this phenomenon. The interactive action strategies to cope with the infodemic include: using health communication components, strengthening social media, verification, speed and transparency, audiences’ communicative empowerment, strengthening convergence, and inter-institutional partnership. At the end, the consequences of the COVID 19 infodemic were discussed and classified into three categories: Communication Consequences; Social, Cultural, and economic consequences, and Health Consequences.

Keywords

Main Subjects


  • Ashrafi-rizi, H., & Kazempour, Z. (2020). Information Typology in Coronavirus (COVID-19) Crisis; a Commentary. Archives of Academic Emergency Medicine8(1), e19. https://doi.org/10.22037/aaem.v8i1.591
  • Bastani, P., & Bahrami, M. A. (2020). COVID-19 Related Misinformation on Social Media: A Qualitative Study from Iran. Journal of medical Internet research, 10.2196/18932. Advance online publication. https://doi.org/10.2196/18932
  • Brainard, J. S, & Hunter, P. R. (2020). Misinformation making a disease outbreak worse: outcomes compared for influenza, monkeypox, and norovirus. Simulation96(4), 365–374. https://doi.org/10.1177/0037549719885021.
  • Brennen, J. S., Simon, F. M., Howard, P. N., & Nielsen, R. K. (2020). Types, sources, and claims of COVID-19 misinformation. Reuters Institute, 7(3), 1.
  • Depoux, A., Martin, S., Karafillakis, E., Preet, R., Wilder-Smith, A., & Larson, H. (2020). The pandemic of social media panic travels faster than the COVID-19 outbreak. Journal of travel medicine27(3), taaa031. https://doi.org/10.1093/jtm/taaa031.
  • Ferasatkhah, M. (2020) Qualitative Research Method in Social Sciences emphasizing Grounded Theory (10th Ed.). Tehran: Agah. (In Persian)
  • Ferrara, E. (2020). What types of COVID-19 conspiracies are populated by Twitter bots?. First Monday, 25(6). https://doi.org/10.5210/fm.v25i6.10633 .
  • Gallotti, R., Valle, F., Castaldo, N., Sacco, P., & De Domenico, M. (2020). Assessing the risks of 'infodemics' in response to COVID-19 epidemics. Nature human behaviour4(12), 1285–1293. https://doi.org/10.1038/s41562-020-00994-6.
  • Golafshani, N. (2003). Understanding Reliability and Validity in Qualitative Research. The Qualitative Report, 8(4), 597-606. https://doi.org/10.46743/2160-3715/2003.1870.
  • Guba, E. G., & Lincoln, Y. S. (2000). Epistemological and methodological bases of naturalistic inquiry. Educational Communications and Technology Journal (ECTJ), 30(4), 233-252.
  • Kouzy, R., Abi Jaoude, J., Kraitem, A., El Alam, M. B., Karam, B., Adib, E., Zarka, J., Traboulsi, C., Akl, E. W., & Baddour, K. (2020). Coronavirus Goes Viral: Quantifying the COVID-19 Misinformation Epidemic on Twitter. Cureus12(3), e7255. https://doi.org/10.7759/cureus.7255.
  • Li, H. O., Bailey, A., Huynh, D., & Chan, J. (2020). YouTube as a source of information on COVID-19: a pandemic of misinformation?. BMJ Global Health5(5), e002604. https://doi.org/10.1136/bmjgh-2020-002604.
  • Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention. Psychological Science31(7), 770–780. https://doi.org/10.1177/0956797620939054.
  • Safari, H., (2021). Infodemic of Corona in Farsi social media. Quarterly Journal of Applied Studies in Social Sciences and Sociology, 4(17), 63-76. (In Persian)
  • Schaake M. (2020) Coronavirus shows Big Tech can fight ‘infodemic’ of fake news [Internet]. Financial Times; [cited 2020 Mar 23]. Available from: https://www.ft.com/content/b2e2010e-6cf8-11ea-89df-41bea055720b
  • Tangcharoensathien, V., Calleja, N., Nguyen, T., Purnat, T., D'Agostino, M., Garcia-Saiso, S., Landry, M., Rashidian, A., Hamilton, C., AbdAllah, A., Ghiga, I., Hill, A., Hougendobler, D., van Andel, J., Nunn, M., Brooks, I., Sacco, P. L., De Domenico, M., Mai, P., Gruzd, A., … Briand, S. (2020). Framework for Managing the COVID-19 Infodemic: Methods and Results of an Online, Crowdsourced WHO Technical Consultation. Journal of medical Internet research22(6), e19659. https://doi.org/10.2196/19659.
  • Wang, Y., McKee, M., Torbica, A., & Stuckler, D. (2019). Systematic literature review on the spread of health-related misinformation on social media. Social Science & Medicine, 240, 112552. https://doi.org/10.1016/j.socscimed.2019.112552.
  • Williamson K. M. (2009). Evidence-based practice: critical appraisal of qualitative evidence. Journal of the American Psychiatric Nurses Association15(3), 202–207. https://doi.org/10.1177/1078390309338733.
  • Zarocostas J. (2020). How to fight an infodemic. Lancet (London, England)395(10225), 676. https://doi.org/10.1016/S0140-6736(20)30461-X.