Examining How Fact-checking Hubs Counter Information Disorder in Africa
DOI:
https://doi.org/10.18196/jkm.v17i1.25725Keywords:
Fake News, Information Disorder, Fact-Checking, AfricaAbstract
As fake news, misinformation, and communication disorders continue to raise societal concerns, several countermeasures are emerging to combat this growing challenge. This study examines the role of social media in the spread of information disorder in Africa and evaluates how effectively three prominent fact-checking websites—FactCheckHub, Dubawa, and Africa Check—are addressing this communication crisis. Using a content analysis methodology, the research identifies common types of misinformation circulating on Nigerian social media, analyzes existing fact-checking techniques, and assesses the contributions of the selected platforms in mitigating information disorder. Drawing on academic frameworks related to misinformation, disinformation, and verification, the study explores how social media facilitates the spread of false narratives and the societal consequences that ensue. It contributes to broader discussions on media literacy, information integrity, and the cultivation of an informed society in the digital age by providing insights into the dynamics of disinformation in Nigeria and the critical role of fact-checking initiatives in addressing it.
References
Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211–236. https://doi.org/10.1257/jep.31.2.211
Amazeen, M. A. (2020). Journalistic interventions: The structural factors affecting the global emergence of fact-checking. Journalism, 21(1), 95–111. https://doi.org/10.1177/1464884917730217
Auxier, B., & Anderson, M. (2021). Social media use in 2021. Pew Research Center. https://www.pewresearch.org/internet/2021/04/07/social-media-use-in-2021/
Bakir, V., & McStay, A. (2018). Fake news and the economy of emotions: Problems, causes, solutions. Digital Journalism, 6(2), 154–175. https://doi.org/10.1080/21670811.2017.1345645
Bradshaw, S., & Howard, P. N. (2019). The global disinformation order: 2019 global inventory of organised social media manipulation. Project on Computational Propaganda. https://comprop.oii.ox.ac.uk/research/cybertroops2019/
Brennen, J. S., Simon, F., Howard, P. N., & Nielsen, R. K. (2020). Types, sources, and claims of COVID-19 misinformation. Reuters Institute. https://reutersinstitute.politics.ox.ac.uk/types-sources-and-claims-covid-19-misinformation
Bridgman, A., Merkley, E., Loewen, P. J., Owen, T., Ruths, D., Teichmann, L., & Zhilin, O. (2020). The causes and consequences of COVID-19 misperceptions: Understanding the role of news and social media. Harvard Kennedy School Misinformation Review, 1(3). https://doi.org/10.37016/mr-2020-028
Cheruiyot, D., & Ferrer-Conill, R. (2018). “Fact-checking Africa”: Epistemologies, data and the expansion of journalistic discourse. Digital Journalism, 6(8), 964–975. https://doi.org/10.1080/21670811.2018.1493940
Chiluwa, I. E., & Ifukor, P. (2015). ‘War against our children’: Stance and evaluation in #BringBackOurGirls campaign discourse on Twitter and Facebook. Discourse & Society, 26(3), 267–296. https://doi.org/10.1177/0957926514564737
Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C. M., Brugnoli, E., Schmidt, A. L., ... & Scala, A. (2020). The COVID-19 social media infodemic. Scientific Reports, 10(1), 1–10. https://doi.org/10.1038/s41598-020-73510-5
Cunliffe-Jones, P. (2022). The rise of fact-checking in Africa. Digital Journalism, 10(1), 55–77. https://doi.org/10.1080/21670811.2021.1989315
Fallis, D. (2015). What is disinformation? Library Trends, 63(3), 401–426. https://doi.org/10.1353/lib.2015.0014
Graves, L. (2016). Deciding what’s true: The rise of political fact-checking in American journalism. Columbia University Press.
Graves, L. (2018). Understanding the promise and limits of automated fact-checking. Reuters Institute for the Study of Journalism. https://reutersinstitute.politics.ox.ac.uk/our-research/understanding-promise-and-limits-automated-fact-checking
Graves, L., & Cherubini, F. (2016). The rise of fact-checking sites in Europe. Reuters Institute for the Study of Journalism. https://reutersinstitute.politics.ox.ac.uk/our-research/rise-fact-checking-sites-europe
Hassan, N., Arslan, F., Li, C., & Tremayne, M. (2019). Toward automated fact-checking: Detecting check-worthy factual claims by ClaimBuster. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 1803–1812. https://doi.org/10.1145/3292500.3330665
Highfield, T., & Leaver, T. (2016). Instagrammatics and digital methods: Studying visual social media, from selfies and GIFs to memes and emoji. Communication Research and Practice, 2(1), 47–62. https://doi.org/10.1080/22041451.2016.1155332
Krippendorff, K. (2022). Content analysis: An introduction to its methodology (4th ed.). Sage. https://methods.sagepub.com/book/mono/content-analysis-4e/toc
Lewandowsky, S., Ecker, U. K., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and its correction: Continued influence and successful debiasing. Psychological Science in the Public Interest, 13(3), 106–131. https://doi.org/10.1177/1529100612451018
Neuendorf, K. A. (2017). The content analysis guidebook (2nd ed.). Sage. https://methods.sagepub.com/book/mono/the-content-analysis-guidebook-2e/toc
Nnanwube, E. F., Ani, K. J., & Ojakorotu, V. (2020). Social media, fake news and the 2019 general elections in Nigeria. African Renaissance, 17(1), 11–26.
Nyhan, B., & Reifler, J. (2015). The effect of fact-checking on elites: A field experiment on US state legislators. American Journal of Political Science, 59(3), 628–640. https://doi.org/10.1111/ajps.12162
Okoro, E. M., & Okolie, U. C. (2021). Analysis of social media misinformation during COVID-19 pandemic in Nigeria. Journal of Contemporary African Studies, 39(2), 291–308. https://doi.org/10.1080/02589001.2021.1926310
Oyeyemi, S. O., Gabarron, E., & Wynn, R. (2014). Ebola, Twitter, and misinformation: A dangerous combination? BMJ, 349, g6178. https://doi.org/10.1136/bmj.g6178
Pennycook, G., & Rand, D. G. (2019). Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences, 116(7), 2521–2526. https://doi.org/10.1073/pnas.1806781116
Resende, G., Melo, P., Sousa, H., Messias, J., Vasconcelos, M., Almeida, J., & Benevenuto, F. (2019). (Mis)Information dissemination in WhatsApp: Gathering, analyzing and countermeasures. The World Wide Web Conference, 818–828. https://doi.org/10.1145/3308558.3313688
Spohr, D. (2017). Fake news and ideological polarization: Filter bubbles and selective exposure on social media. Business Information Review, 34(3), 150–160. https://doi.org/10.1177/0266382117722446
Stencel, M., & Perry, K. (2016). Superpowers: The digital skills media leaders say newsrooms need going forward. Tow-Knight Center for Entrepreneurial Journalism. https://webdesign.cindyroyal.net/handouts/Superpowers_%20Digital%20Skills%20Newsrooms%20Need_.pdf
Tandoc, E. C., Jenkins, J., & Craft, S. (2020). A typology of fake news: A multidimensional examination of different types of fake news based on content, intent, and source. Journalism Studies, 21(9), 1130–1153. https://doi.org/10.1080/1461670X.2020.1807378
Vaccari, C., & Chadwick, A. (2020). Deepfakes and disinformation: Exploring the impact of synthetic political video on deception, uncertainty, and trust in news. Social Media + Society, 6(1), 2056305120903408. https://doi.org/10.1177/2056305120903408
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559
Walter, N., Cohen, J., Holbert, R. L., & Morag, Y. (2020). Fact-checking: A meta-analysis of what works and for whom. Political Communication, 37(3), 350–375. https://doi.org/10.1080/10584609.2019.1668894
Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe. https://edoc.coe.int/en/media/7495-information-disorder-toward-an-interdisciplinary-framework-for-research-and-policy-making.html
Wasserman, H., & Madrid-Morales, D. (2019). An exploratory study of “fake news” and media trust in Kenya, Nigeria and South Africa. African Journalism Studies, 40(1), 107–123. https://doi.org/10.1080/23743670.2019.1627230
Woolley, S. C., & Howard, P. N. (2018). Computational propaganda: Political parties, politicians, and political manipulation on social media. Oxford University Press. https://academic.oup.com/book/25859
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Komunikator

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Komunikator as publisher of the journal. Copyright encompasses rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.
Authors should sign Copyright Transfer Agreement when they have approved the final proofs sent by Komunikator prior the publication. Komunikator strive to ensure that no errors occur in the articles that have been published, both data errors and statements in the article.
Komunikator keep the rights to articles that have been published. Authors are allowed to use their works for any purposes deemed necessary without written permission from Komunikator with an acknowledgement of initial publication in this journal.
License
All articles published in Komunikator are licensed under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA) license. You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.