Probability or score on how likely an article is motivated by content marketing
If you have a broad set of testing data, I think this is feasible. I've had luck in getting basic models to identify abstract concepts like someone's politics or real news vs fake news, so I think this could work if people write content marketing different from normal news.

I just used this link in another post, but here is a tutorial in Python of taking unstructured articles, passing them through an NLP pipeline, and classifying them into multiple groups.