Author
Listed:
- Catherine Mei Ling Wong
- Yuanyuan Wu
Abstract
The COVID-19 pandemic laid bare the problem of fake news as one of the defining challenges of our time. The sudden proliferation of fake news and its direct impact on public health and safety led to increasing attention to pre-bunking interventions as a possible tool against the risks of fake news. These studies claimed that it is possible to use pre-emptive interventions such as games to induce cognitive resistance against the deception techniques deployed by fake new producers. We wanted to test if this method could be as effective in a non-Western context, and in an on-going catastrophic risk event. This paper presents the results of a replication study of Roozenbeek and van der Linden’s gaming experiment with certain modifications tailored to the case of Singapore in 2020 in the midst of the COVID-19 pandemic. We could not replicate the results of the original study. However, we found factors that could have accounted for the different results, including high levels of trust in English mainstream media and the government, and positive attitudes towards censorship. We also found that participants were most resistant against conspiratorial deception techniques but also more vulnerable to impersonation techniques. We reflect on what the results of our study say about the limitations of psychology-focused interventions and the need for a wider suite of interventions targeting different levels of analysis, including sociological factors and the risk context.
Suggested Citation
Catherine Mei Ling Wong & Yuanyuan Wu, 2023.
"Limits to inoculating against the risk of fake news: a replication study in Singapore during COVID-19,"
Journal of Risk Research, Taylor & Francis Journals, vol. 26(10), pages 1037-1052, October.
Handle:
RePEc:taf:jriskr:v:26:y:2023:i:10:p:1037-1052
DOI: 10.1080/13669877.2023.2249909
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jriskr:v:26:y:2023:i:10:p:1037-1052. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RJRR20 .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.