It takes a village to identify false news

Filloux: A credibility scorecard
Liberal democracies are being tested around the world by the rapid diffusion of misleading or false information designed to influence voters.

It has happened in France, Catalonia, the U.K., and, of course, the U.S.

Many have proposed--for example, the World Economic Forum--that two of the most powerful vehicles for spreading information, Facebook and Google, should be responsible for filtering out material that is demonstrably false or misleading.

Versión en español. 

But it turns out that this is not easy to do. False information is often irresistibly appealing and moves too fast to be stopped.
Why we're Still in the Dark about Facebook's Fight Against Fake News -- Mother Jones
Nine experts offer opinions on how to fix Facebook -- New York Times

Not an editor, but a scorecard

What's more, it is hard to define false news in a way that can be automated by algorithms. Journalist and media consultant Frederic Filloux has developed the News Quality Scoring Project, which attempts to use automated systems to evaluate the likely credibility of a piece of news content. It doesn't label news as false or fake. It simply gives a credibility score based on a series of indicators such as a publisher's or a journalist's previous reliability.

Filloux's Publication Quality Score criteria

Facebook, Google, and Twitter themselves are working with the Trust Project on an automated system to display "trust indicators" alongside information they share with users.

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