How do you distinguish between conversational text and possible news article?
News sentences will have more unique tokens than normal conversations.
Conversations have more stop words than news articles.

I think you can use bert or normal wordvect classification to train a baseline model here.
I would play aroud the pipeline  of fake news classifier and news-conversation classifier. like passing the text to news classifier first and then passing it to news-conversation classifier. Try to mix and match to get the best results. Set some thresholds.