Inoculating Against An #Infodemic - Don't Be Fooled by Covid-19 Misinformation

As health officials around the world grapple with a pandemic caused by a new coronavirus, COVID-19, they are also facing a deluge of misinformation about the virus on traditional and social media. The World Health Organization is calling this phenomenon an “infodemic” – “an overabundance of information—some accurate and some not—that makes it hard for people to find trustworthy sources and reliable guidance when they need it.” To help stem the tide of COVID-19 misinformation, our team of computational social scientists, communications professionals and developers are developing various real-time information dashboards to keep track of false COVID-19 claims. Our  various misinformation dashboards track and visualize debunked coronavirus claims from an international network of trusted fact checkers. Browse through to see the latest debunked COVID-19 false claims from around the world. 

Tracks and visualizes debunked coronavirus claims from a network of trusted fact checkers from around the world. 

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Tracks and visualizes debunked coronavirus claims mentioning or associated with a specific geographic location.

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Tracks and visualizes coronavirus misinformation news stories published by media organizations in Canada.

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Twelve Common Types of COVID-19 Misinformation

Based on our manual review of over 4000+ debunked claims with keywords “COVID” or “Coronavirus”, here are the 12 most common types of COVID-19 misinformation that are currently making  the rounds online:

COVID-19 Misinformation Types Coding Schema & Dashboard

The COVID-19 Misinformation Types Coding Schema includes 12 of the most common types of COVID-19 misinformation and their definitions. The coding schema was developed based on our manual review of thousands of debunked claims containing keywords “COVID” or “Coronavirus” (as recorded by the Google Fact Check Tools since January 22, 2020). 
The coding schema was developed to facilitate a systematic review and grouping of similar claims under the same claim type. By applying the coding schema, researchers can study the types of claims that are circulating online and offline, their prevalence and persistence over time. The coding schema can also inform work by policy makers and developers when implementing different mitigation strategies in response to different claim types. An earlier version of this coding schema, with just seven categories, was published in Policy Options Magazine on April 14, 2020.
Citation: Gruzd, A. & Mai, P. (2020). COVID-19 Misinformation Types Coding Schema, Version 2.0. Ryerson University Social Media Lab.* 
*Note: The interactive dashboard and the accompanying  coding schema are work-in-progress. As we’re iteratively cleaning the source data and improving the coding schema to refine definitions and reconciling coding results between our coders, counts and percentages may change slightly over time. When citing the following charts, please include the “Accessed on” date in the citation. 

Semantic Connections among COVID-19 Fact-checked Claims

Click on the network picture below to see an interactive visualization of different themes and semantic connections among 2,400 pieces of  fact-checked #COVID19 claims.

Additional Fact Checking Resources

Also check out the following awesome misinformation resources to inoculate yourself against an infodemic:

For up-to-date information and additional resources on COVID-19, visit the Public Health Agency of Canada.