Poynter – Automated fact-checking can catch claims that slip past human checkers. Here are the two ways they work. They either verify claims by validating them against an authoritative source or article, or use a computing technique called stance detection. “From false claims that drinking warm water with lemon protects against the coronavirus to high contamination rates among NATO troops based in Latvia, the pandemic has been ripe for many kinds of hoaxes and disinformation campaigns. Between January and March, the Reuters Institute for the Study of Journalism noticed that the number of fact-checks rose by 900%, which probably means an even higher increase in fake news occurrences since many of them likely slipped through the net. Although media literacy is essential to turning the tide, the use of automation and algorithms could help conduct fact-checking efforts at scale. In his 2018 report, Lucas Graves essentially identified two types of automated fact-checking: fact-checks that verify claims by validating them against an authoritative source or a story that had already been verified, and fact-checks that rely on “secondary signals” such as stance detection — a computing technique that determines whether a piece of text agrees or disagrees with a claim. Here is an overview of journalistic uses and research projects looking at both aspects…”