Absolutely. There is all sorts of methods that can be employed. Facts can be obfuscated, I suppose a natural language model might be able to detect if this is u

Absolutely. There is all sorts of methods that can be employed. Facts can be obfuscated, I suppose a natural language model might be able to detect if this is unusual for that source but it doesn’t mean fake news. Another is simply lying with statistics, this would be much harder for NLP as now your talking getting the model to understand statistically information, understanding the background and why certain ways of presenting stats might be disingenuous for that subject. You are also just relying on a model that only its owner could verify. Ultimately though, this is fighting a losing battle because the source of the issue isn’t in propaganda which has long existed but in the channels through which it spreads. Something that has been known for a long time is flaming passions is more effective than fact. So too for social media is the spread of information faster when false[https://www.smithsonianmag.com/smart-news/fake-news-spreads-faster-and-deeper-verified-stories-180968443/ https://www.smithsonianmag.com/smart-news/fake-news-spreads-...]. Which makes it difficult to counteract if the false information spreads faster than the rebuttal.