There is as yet very little known about technological measures specifically targeted at Covid-19 fake news, but fortunately, there are a great many initiatives relating to technological measures against fake news in general, which may also be deployed to combat Covid-19 fake news. 

National and international reports have been published over the past years about the measures that can be taken to combat news. See for example A multi-dimensional approach to disinformation. Report of the independent High level Group on fake news and online disinformation dat de Europese Commissie in 2018 publiceerde. A multi-dimensional approach to disinformation – Publications Office of the EU (

See also Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe27. PREMS-162317-GBR-2018-Report-desinformation-A4-BAT.pdf (

Fact checking is often cited as a solution to fight fake news. See the following fact-checking projects: and Fact- Checking – Duke Reporters’ Lab (

The EU, too, is working on fact-checking projects. “The advisory board and our pool of assessors. The International Fact-Checking Network has seven counselors who represent the geographical diversity of the network. They are pioneers in the development and implementation of fact-checking in their countries and regions. All board members are unpaid. The pool of assessors is a group of journalism and media experts who know the fact-checking context in their countries and act as the first filter for each application received.”

Since June 2020, the EU has required Facebook, Twitter and Google to produce monthly reports on the fight against fake news on their platforms. Facebook, Twitter, Google to report monthly on fake news fight, EU says | Reuters

👁 See also 2. Fact-checking labels

The sheer  volume of news and the speed with which this is disseminated on a daily basis obviously make it impossible to fact check the news about Covid-19 by hand. In this case, AI-based technological tools may be used to support these efforts. Wikipedia, for example, uses both bots and human editors to correct inaccuracies on the site. Wikipedia:Bot policy – Wikipedia

Automatic fake news detection is another option. The question which then arises is the extent to which automatic fake news detection technology is accurately able to identify ‘incorrect’ news. On a more critical note, care should be taken to ensure absolute transparency regarding who compiled the algorithms and what criteria apply to determine what is true and what is not.


📚 Linguistic and network approaches

Linguistic and network approaches could help to detect fake news automatically:


Most liars use their language strategically to avoid being caught. In spite of the attempt to control what they are saying, language “leakage” occurs with certain verbal aspects that are hard to monitor such as frequencies and patterns of pronoun, conjunction, and negative emotion word usage (Feng & Hirst, 2013). The goal in the linguistic approach is to look for such instances of leakage or, so called “predictive deception cues” found in the content of a message.” Conroy et al. (2015)

Feng, V. & Hirst, G. (2013) Detecting deceptive opinion with profile compatibility.


Innovative and varied, using network properties and behavior are ways to complement content-based approaches that rely on deceptive language and leakage cues to predict deception. As real-time content on current events is increasingly proliferated through micro-blogging applications such as Twitter, deception analysis tools are all the more important.” Conroy et al. (2015)

Conroy, N. J., Rubin, V. L., & Chen, Y. (2015). Automatic deception detection: Methods for finding fake news. Proceedings of the Association for Information Science and Technology, 52(1), 1-4. (11) (PDF) Automatic Deception Detection: Methods for Finding Fake News (

📚 Google News and Google Search

“Google introduced fact-check labels to Google News to allow publishers to highlight fact-checked content and help users find and consult more easily articles that provide a critical outlook on claims made by others. This feature helps support the work of the fact-checking community. This fact-checking feature first appeared in the UK and the US in October 2016 and has since been rolled out globally. Google has expanded the fact-checking labels to Google Search results, to allow publishers to provide greater awareness to users of the tools available to them to consider the accuracy of a story. These labels in Search make it easier for publishers to highlight their fact-checking work that shows users the origin of a claim and clearly display their verdict on the veracity of the claim. This work has been done in collaboration with the fact-check community, and started with a collaboration between the Duke University Report’s Lab and Jigsaw, a team within Alphabet, Google’s parent company. Share the Facts enables fact-checkers to more easily share the claims they looked at and their fact-check findings, and also makes it easier for others to highlight their fact checks, for example in Search results.”

A multi-dimensional approach to disinformation. Report of the independent High level Group on fake news and online disinformation, p. 16 A multi-dimensional approach to disinformation – Publications Office of the EU ( p.16

“Over the last several years, fact checking has come into its own. Led by organizations like the International Fact-Checking Network, rigorous fact checks are now conducted by more than 100 active sites, according to the Duke University Reporter’s Lab. They collectively produce many thousands of fact-checks a year, examining claims around urban legends, politics, health, and the media itself. In the seven years since we started labeling types of articles in Google News (e.g., In-Depth, Opinion, Wikipedia), we’ve heard that many readers enjoy having easy access to a diverse range of content types. Earlier this year, we added a “Local Source” Tag to highlight local coverage of major stories. Today, we’re adding another new tag, “Fact check,” to help readers find fact checking in large news stories. You’ll see the tagged articles in the expanded story box on and in the Google News & Weather iOS and Android apps, starting with the U.S. and the U.K.” Labeling fact-check articles in Google News (



“Facebook has looked at the impact of “Disputed” flags and concluded that they can be counter-productive, which led to its decision to test a new approach based on the automatic display of alternative recommended content (“Related Articles”).”

“Fact-checking has often been proposed as a solution to bridge the information asymmetry between consumers and news providers. Fact-checking only applies to the narrow definition of verifiably false news; it does not address the wider concerns about the quality of online news. Fact-checkers can signal suspicious content to editors who review “flagged” content and possibly remove it or mark it as potentially false news. Pennycook & Rand (2017) conducted five experiments to test the effectiveness of attaching warnings to news stories that have been disputed by third-party fact-checkers. They find that while warnings do lead to a modest reduction in perceived accuracy of fake news relative to a control condition, there is also an implied truth effect: the presence of warnings caused untagged stories to be seen as more accurate than in the control. Fact-checking 49 becomes ineffective when confirmation and desirability bias are prevalent. Another problem with this flagging strategy is that it can take a considerable amount of time to do the flagging, compared with the duration of an average news cycle that does not exceed 48h (Tan et al, 2016) and possibly much shorter for the bulk of sharing on social media websites.”

European Commission (February, 2018). The digital transformation of news media and the rise of disinformation and fake news, pp. 48-49 The digital transformation of news media and the rise of disinformation and fake news | EU Science Hub (

👁 See also: Communicative actions we live by: The problem with fact-checking, tagging or flagging fake news – the case of Facebook – Jack Andersen, Sille Obelitz Søe, 2020 (