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

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dc.contributor.author Mthethwa, Sthembile N
dc.contributor.author Dlamini, Nelisiwe P
dc.contributor.author Mkuzangwe, Nenekazi NP
dc.contributor.author Shibambu, Ncedisa AM
dc.contributor.author Boateng, Thato G
dc.contributor.author Mantsi, Andile M
dc.date.accessioned 2021-11-19T14:02:21Z
dc.date.available 2021-11-19T14:02:21Z
dc.date.issued 2021-09
dc.identifier.citation Mthethwa, S.N., Dlamini, N.P., Mkuzangwe, N.N., Shibambu, N.A., Boateng, T.G. & Mantsi, A.M. 2021. Understanding the Impact of and Analysing Fake News About COVID-19 in SA. <i>Lecture Notes in Computer Science, 12887.</i> http://hdl.handle.net/10204/12162 en_ZA
dc.identifier.isbn 978-3-030-87030-0
dc.identifier.isbn 978-3-030-87031-7
dc.identifier.issn 0302-9743
dc.identifier.uri https://doi.org/10.1007/978-3-030-87031-7_5
dc.identifier.uri http://hdl.handle.net/10204/12162
dc.description.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. en_US
dc.format Abstract en_US
dc.language.iso en en_US
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-030-87031-7_5#citeas en_US
dc.source Lecture Notes in Computer Science, 12887 en_US
dc.subject COVID-19 misinformation en_US
dc.subject Fake news en_US
dc.subject Social media en_US
dc.title Understanding the Impact of and Analysing Fake News About COVID-19 in SA en_US
dc.type Article en_US
dc.description.pages 66-84 en_US
dc.description.note © Springer Nature Switzerland AG 2021. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website: https://doi.org/10.1007/978-3-030-87031-7_5 en_US
dc.description.cluster Defence and Security en_US
dc.description.cluster Smart Places en_US
dc.description.impactarea Information & Cyber Security C en_US
dc.description.impactarea Command Control and Integrated Systems en_US
dc.description.impactarea Urban and Regional Dynamics en_US
dc.identifier.apacitation Mthethwa, S. N., Dlamini, N. P., Mkuzangwe, N. N., Shibambu, N. A., Boateng, T. G., & Mantsi, A. M. (2021). Understanding the Impact of and Analysing Fake News About COVID-19 in SA. <i>Lecture Notes in Computer Science, 12887</i>, http://hdl.handle.net/10204/12162 en_ZA
dc.identifier.chicagocitation Mthethwa, Sthembile N, Nelisiwe P Dlamini, Nenekazi NP Mkuzangwe, Ncedisa AM Shibambu, Thato G Boateng, and Andile M Mantsi "Understanding the Impact of and Analysing Fake News About COVID-19 in SA." <i>Lecture Notes in Computer Science, 12887</i> (2021) http://hdl.handle.net/10204/12162 en_ZA
dc.identifier.vancouvercitation Mthethwa SN, Dlamini NP, Mkuzangwe NN, Shibambu NA, Boateng TG, Mantsi AM. Understanding the Impact of and Analysing Fake News About COVID-19 in SA. Lecture Notes in Computer Science, 12887. 2021; http://hdl.handle.net/10204/12162. en_ZA
dc.identifier.ris TY - Article AU - Mthethwa, Sthembile N AU - Dlamini, Nelisiwe P AU - Mkuzangwe, Nenekazi NP AU - Shibambu, Ncedisa AM AU - Boateng, Thato G AU - Mantsi, Andile M AB - 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. DA - 2021-09 DB - ResearchSpace DP - CSIR J1 - Lecture Notes in Computer Science, 12887 KW - COVID-19 misinformation KW - Fake news KW - Social media LK - https://researchspace.csir.co.za PY - 2021 SM - 978-3-030-87030-0 SM - 978-3-030-87031-7 SM - 0302-9743 T1 - Understanding the Impact of and Analysing Fake News About COVID-19 in SA TI - Understanding the Impact of and Analysing Fake News About COVID-19 in SA UR - http://hdl.handle.net/10204/12162 ER - en_ZA
dc.identifier.worklist 25024 en_US


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