How do you distinguish between conversational text and possible news article? Context

When you receive messages in group chats, how do you detect if that message belongs to conversational dialogue or if it is a 'news' article (could be fake or real) that they are sharing?

Examples

Conversational dialogue: "Does anyone wanna have dinner today? I am pretty free this evening and I don't have dinner at home. Please let me know by 8pm!!"

'News' article: "New Japan’s growth has been helped by YouTube, which has made New Japan’s matches more accessible to an audience outside of Asia, said Dave Meltzer, publisher of the Wrestling Observer Newsletter, which has followed the sport since 1983. Capitalizing on this rise, New Japan launched an online streaming service — similar to the W.W.E. Network — in December 2014."

Question

Would you use rule-based matching or a classifier for this problem? (Assuming you already have a classifier for detecting if the news article is fake or real)
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.