COVID-19 Misinformation Newsletter 27 Jul 2021
27 July 2021
The COVID-19 Misinformation Newsletter is prepared by the staff of the Programme on Democracy and Technology (DemTech) at Oxford University. We summarise the latest independent research and high-quality news reporting on the production and consumption of computational propaganda, fake news, and campaigns to manipulate public understanding of the health crisis.
1. NiemanLab reports an overlooked platform where COVID-19 vaccine misinformation flourishes. Nextdoor is a local platform that has “attracted the same conspiracy-leaning fare that is common on other social media”, though its scale seems to be less extensive than larger platforms.
2. A US health official believes that misinformation is the greatest threat to COVID-19 vaccination efforts, CNN reports. According to Dr Vivek Murthy, the US Surgeon General, “two-thirds of those who are unvaccinated in polls say that they either believe the myths about COVID-19 or think that they might be true.”
3. NPR reports on how anti-vaccination activists used a database of vaccine side effects maintained by US scientists to spread disinformation about COVID-19 vaccines. According to the report, activists manipulated data in order to falsely claim that COVID-19 vaccines are dangerous.
4. Reuters Institute’s Digital News Report finds that people in many countries are more concerned about the behaviours of national politicians when it comes to spreading misleading information about COVID-19 than the actions of foreign governments or ordinary people. At the same time, on average more people have seen false and misleading information about coronavirus (54%) than they have about politics (43%). Among digital platforms, Facebook and WhatsApp draw the most concern across all markets studied when it comes to COVID-19 misinformation.
5. Big Data and Society publishes an overview of opportunities for applying technology to study and combat disinformation. The overview proposes the following technology solutions: data and text-mining methods in misinformation detection, sentiment analysis, complex networks, machine learning and agent-based models of misinformation spreading, and the detection of misinformation sources in the network.
6. Journal of Public Health publishes a large review of studies on misinformation during large-scale infectious disease outbreaks. It finds that lack of trust in the government and a lack of scientific knowledge increased the consumption of misinformation. Vaccines were particularly common subjects of misinformation campaigns, while women and youth audiences were found to be especially vulnerable to such campaigns.
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