While reviewing works concerning automatic fake news detection, I discovered that some papers tend to divide the topic into two approaches: data-mining-oriented and NLP-oriented (both using ML).

I'm not sure what's the difference, since NLP too can use hand-crafted features obtained by data mining. Can someone explain me how these approaches differ?