Many practical fake news detection algorithms use a kind of semantic side information, such as whether the generated text is factually correct, in addition to its statistical properties. Although statistical side information would be straightforward to incorporate in the hypothesis testing framework, it remains to understand how to cast such semantic knowledge in a statistical decision theory framework. 
 Question: What semantic features help in detecting whether a piece of text is genuine or generated? of 
No feature is given, only discussion that semantic features are use in practice and yet to be discovered how to embed that knowledge into statistical decision theory framework.