Skip to main content

Understanding the Impact of and Analysing Fake News About COVID-19 in SA

  • Conference paper
  • First Online:
Disinformation in Open Online Media (MISDOOM 2021)

Abstract

The topic of fake news is not new but its rise is fueled by the digital age era. The increased proliferation of fake news has been observed since the coronavirus disease 2019 (COVID-19) started, thus introducing controversy regarding its origin, conspiracies about 5G causing COVID-19 and COVID-19 home remedies or prevention methods. This information may be harmless, or could potentially pose a threat by misleading the population to depend on unjustified and unsubstantiated claims. Several studies worldwide are investing towards this topic, however, very little has been done in the South African context. Therefore, this study aims at analysing fake news about COVID-19 spread during the South African national lockdown on social media platforms and news outlets; together with the measures put in place by the government i.e. social relief funds and food parcels. This study took place between March 2020 and October 2020 whereby a Google form was used to collect data. The collected data was verified using fact-checking websites like Africa Check and techniques such as Google reverse image for image verification. Thereafter, the data was coded according to these categories, namely; misinformation, disinformation, malinformation, propaganda and scams, and annotated according to 11 annotation classes. The analysis showed that Twitter was the leading source of fake news at 59% followed by WhatsApp at 22%. In addition, most discussions were in reference to COVID-19 cures and treatments. Overtime, a correlation was observed between events (e.g., change in regulations) that occurred and the spread of fake news. To dispel and delegitimise the sources, a publicly accessible dashboard was created where all verified fake news were shared for easier access. This study has established an understanding of the nature of fake news and draws insights that offer practical guidance on how fake news may be combated in the future.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Knowledge@Wharton: “The Impact of Social Media: Is it Irreplaceable?” 26 July 2019. https://knowledge.wharton.upenn.edu/article/impact-of-social-media/. Accessed 18 Nov 2020

  2. Hudson, M.: What Is Social Media? Definition and Examples of Social Media, 23 June 2020. https://www.thebalancesmb.com/what-is-social-media-2890301

  3. Zhou, X., Zafarani, R.: A survey of fake news: fundamental theories, detection methods, and opportunities. ACM Comput. Surv. 53(5), 1–40 (2020). https://doi.org/10.1145/3395046

  4. Lazer, D.M.J., et al.: The science of fake news. Science (80-. ). 359(6380), 1094–1096 (2018). https://doi.org/10.1126/science.aao2998

  5. Gottfried, J., Shearer, E.: News Use Across Social Media Platforms 2016, 26 MAY 2016. https://www.journalism.org/2016/05/26/news-use-across-social-media-platforms-2016/

  6. WHO: WHO Director-General’s opening remarks at the media briefing on COVID-19, 30 November 2020. https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---30-november-2020

  7. Cucinotta, D., Vanelli, M.: WHO Declares COVID-19 a Pandemic, 19 March 2020. https://pubmed.ncbi.nlm.nih.gov/32191675/. Accessed 17 Nov 2020

  8. Zarocostas, J.: How to fight an infodemic. Lancet (Lond. Engl.) 395(10225), 676 (2020). https://doi.org/10.1016/S0140-6736(20)30461-X

    Article  Google Scholar 

  9. Pennycook, G., McPhetres, J., Zhang, Y., Lu, J.G., Rand, D.G.: Fighting COVID-19 misinformation on social media: experimental evidence for a scalable accuracy-nudge intervention. Psychol. Sci. 31(7), 770–780 (2020). https://doi.org/10.1177/0956797620939054

    Article  Google Scholar 

  10. Frenkel, S., Alba, D., Zhong, R.: Surge of Virus Misinformation Stumps Facebook and Twitter. The New York Times (2020). https://www.nytimes.com/2020/03/08/technology/coronavirus-misinformation-social-media.html

  11. Lampos, V., et al.: Tracking COVID-19 using online search, no. July 2020. http://arxiv.org/abs/2003.08086

  12. Pulido, C.M., Ruiz-Eugenio, L., Redondo-Sama, G., Villarejo-Carballido, B.: A new application of social impact in social media for overcoming fake news in health. Int. J. Environ. Res. Public Health 17(7), 2430 (2020). https://doi.org/10.3390/ijerph17072430

  13. Statistics South Africa. Mid-year population estimates 2020. Statistical Release P0302. [online] Pretoria: Statistics South Africa, pp. 8–9 (2021). http://www.statssa.gov.za/publications/P0302/P03022020.pdf

  14. Miniwatts Marketing Group: “Internet Users Statistics for Africa (Africa Internet Usage, 2020 Population Stats and Facebook Subscribers)”, 12 November 2020. https://www.internetworldstats.com/stats1.htm. Accessed 30 Nov 2020

  15. Al-Zaman, M.S.: COVID-19-related fake news in social media. SSRN Electron. J. 1–12 (2020). https://doi.org/10.2139/ssrn.3644107

  16. Memon, S.A., Carley, K.M.: Characterizing COVID-19 misinformation communities using a novel twitter dataset. In: CEUR Workshop Proceedings, vol. 2699 (2020)

    Google Scholar 

  17. Duffy, A., Tandoc, E., Ling, R.: Too good to be true, too good not to share: the social utility of fake news. Inf. Commun. Soc. 23(13), 1965–1979 (2020). https://doi.org/10.1080/1369118X.2019.1623904

    Article  Google Scholar 

  18. Wardle, C., Derakhshan, H.: Thinking about ‘information disorder’: formats of misinformation, disinformation, and mal-information. J. “fake news” disinformation-UNESCO 43–54 (2018). https://en.unesco.org/sites/default/files/f._jfnd_handbook_module_2.pdf

  19. Egelhofer, J.L., Lecheler, S.: Fake news as a two-dimensional phenomenon: a framework and research agenda. Ann. Int. Commun. Assoc. 43(2), 97–116 (2019). https://doi.org/10.1080/23808985.2019.1602782

    Article  Google Scholar 

  20. Apuke, O.D., Omar, B.: Fake news and COVID-19: modelling the predictors of fake news sharing among social media users. Telemat. Inform. 56(July 2020), 101475 (2021). https://doi.org/10.1016/j.tele.2020.101475

  21. Walczyk, J.J., Igou, F.P., Dixon, A.P., Tcholakian, T.: Advancing lie detection by inducing cognitive load on liars: a review of relevant theories and techniques guided by lessons from polygraph-based approaches. Front. Psychol. 4(February), 1–13 (2013). https://doi.org/10.3389/fpsyg.2013.00014

    Article  Google Scholar 

  22. Russonello, G.: Afraid of Coronavirus? That Might Say Something About Your Politics, The New York Times (2020). https://www.nytimes.com/2020/03/13/us/politics/coronavirus-trump-polling.html

  23. Huynh, T.L.D.: The COVID-19 risk perception: a survey on socioeconomics and media attention. Econ. Bull. 40(1), 1–8 (2020)

    Google Scholar 

  24. Ryder, H.: AFRICA ONLOOKS COVID-19 is only slowly reaching Africa. That’s no surprise. The Africa Report (2020). https://www.theafricareport.com/24160/covid-19-is-only-slowly-reaching-africa-thats-no-surprise/

  25. Ahinkorah, B.O., Ameyaw, E.K., Hagan, J.E., Seidu, A.-A., Schack, T.: Rising above misinformation or fake news in Africa: another strategy to control COVID-19 spread. Front. Commun. 5(June), 2018–2021 (2020). https://doi.org/10.3389/fcomm.2020.00045

    Article  Google Scholar 

  26. Alpert, L.I.: Coronavirus misinformation spreads on Facebook. Watchdog Says, 20 April 2020. https://www.wsj.com/articles/coronavirus-misinformation-spreads-on-facebook-watchdog-says-11587436159

  27. Sahu, K.K., Mishra, A.K., Lal, A.: Comprehensive update on current outbreak of novel coronavirus infection (2019-nCoV). Ann. Transl. Med. 8(6), 393 (2020). https://doi.org/10.21037/atm.2020.02.92

    Article  Google Scholar 

  28. Karlova, N., Fisher, K.: A social diffusion model of misinformation and disinformation for understanding human information behavior. Inf. Res. 18(1), 4 (2013). http://informationr.net/ir/18-1/paper573.html#.YAqh7-gzZPY

  29. Volkova, S., Jang, J.Y.: Misleading or falsification: inferring deceptive strategies and types in online news and social media. In: Web Conference 2018 - Companion World Wide Web Conference WWW 2018, pp. 575–583 (2018). https://doi.org/10.1145/3184558.3188728

  30. Pierri, F., Ceri, S.: False news on social media: a data-driven survey. SIGMOD Rec. 48(2), 18–32 (2019). https://doi.org/10.1145/3377330.3377334

    Article  Google Scholar 

  31. Volkova, S., Shaffer, K., Jang, J.Y., Hodas, N.: Separating facts from fiction: linguistic models to classify suspicious and trusted news posts on twitter. In: ACL 2017 - Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Long Papers), vol. 2, pp. 647–653 (2017). https://doi.org/10.18653/v1/P17-2102

  32. “Merriam-Webster,” (2021). https://www.merriam-webster.com/dictionary/scams

  33. “Fotoforensics,” (2021). http://fotoforensics.com/

  34. Beck, T.S.: How to Detect Image Manipulations Part I - Error Level Analysis in Practice. HEADT Centre (2017). https://headt.eu/How-to-Detect-Image-Manipulations-Part-1. Accessed 20 Jan 2007

  35. “Twitter Analytics” (2021). https://foller.me/

  36. Komendantova, N., et al.: A value-driven approach to addressing misinformation in social media. Humanit. Soc. Sci. Commun. 8(1), 1–12(2021). https://doi.org/10.1057/s41599-020-00702-9

  37. “Virustotal” (2021). https://www.virustotal.com/

  38. Menéndez, H.D., Clark, D., Barr, E.T.: Getting ahead of the arms race: hothousing the coevolution of virustotal with a packer. Entropy 23(4), 1–19 (2021). https://doi.org/10.3390/e23040395

    Article  Google Scholar 

  39. Bloomberg, A.S., Tseng, T., Analyst, L., Law, B., Stent, A., Maida, D.: Best Practices for Managing Data Annotation Projects Best Practices for Managing Data Annotation Projects Chief Data Officer, Global Data Best Practices for Managing Data Annotation Projects, no. September, pp. 1–34 (2020). https://www.researchgate.net/publication/344343972

  40. Pagel, J., Reiter, N., Rösiger, I., Schulz, S.: A unified text annotation workflow for diverse goals. In: CEUR Workshop Proceedings, vol. 2155, pp. 31–36 (2018)

    Google Scholar 

  41. Schreiner, C., Torkkola, K., Gardner, M., Zhang, K.: Using machine learning techniques to reduce data annotation time. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, no. October, pp. 2438–2442 (2006). https://doi.org/10.1177/154193120605002219

  42. Pick, S., Weyers, B., Hentschel, B., Kuhlen, T.W.: Design and evaluation of data annotation workflows for cave-like virtual environments. IEEE Trans. Vis. Comput. Graph. 22(4), 1452–1461 (2016). https://doi.org/10.1109/TVCG.2016.2518086

    Article  Google Scholar 

  43. Bengtsson, M.: How to plan and perform a qualitative study using content analysis. NursingPlus Open 2, 8–14 (2016). https://doi.org/10.1016/j.npls.2016.01.001

    Article  Google Scholar 

  44. Samal, J.: Impact of COVID-19 infodemic on psychological wellbeing and vaccine hesitancy. Egypt. J. Bronchol. 15(1), 1–6 (2021). https://doi.org/10.1186/s43168-021-00061-2

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sthembile Mthethwa .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mthethwa, S., Dlamini, N., Mkuzangwe, N., Shibambu, A., Boateng, T., Mantsi, M. (2021). Understanding the Impact of and Analysing Fake News About COVID-19 in SA. In: Bright, J., Giachanou, A., Spaiser, V., Spezzano, F., George, A., Pavliuc, A. (eds) Disinformation in Open Online Media. MISDOOM 2021. Lecture Notes in Computer Science(), vol 12887. Springer, Cham. https://doi.org/10.1007/978-3-030-87031-7_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-87031-7_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87030-0

  • Online ISBN: 978-3-030-87031-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics