How would language and grammar detection aid in fake news detection? What makes news "fake" generally involves dimensions far more complex than grammar.
Well if I ever start following the textbook rules about the Oxford comma and splint infinitives, that's when you'll know I've been replaced with a Russian bot.
In seriousness, language/grammar use analysis could potentially provide a hint that the person behind a user account has been replaced by another writer.
I did not say that language and grammar detection would help in fake news detection. What I meant was shouldn’t fake news detection be the next logical step after language and grammar detection.
No this is nonsense. You could, at best, train a model to either identify specific fake news claims; or perhaps train it to identify the style of one particular fake news source. But you will never create a model that can identify novel claims from an author you don't have a strong reason to associate with fake/genuine news beforehand.
How could that possibly work? Not even holmes was so bold in his claims of linguistic analysis.
It’s not entirely nonsense. Not all fake news is social engineering but almost all social engineering has some ‘fake news’ component.
If you can use NLP for detecting social engineering scams, it can also be used to detect fake news. There will likely be false positives. But that’s because the net would be wide.
No it is absolutely nonsense. You cannot possibly use NLP to evaluate novel claims and evaluate them for truthfulness. The NLP model couldn't know that. Social engineering is detectable because it usually includes something like a request for your personal information.
A novel fake news claim would not look anything like prior fake news claims. You'll have false positives, yes. You'll also have false negatives. Probably a lot of them.
A generic fake news detector is very different from, say, a detector of claims that Ukraine is a nazi state. The latter is easy to detect.
