One of the most fundamental concerns when envisioning methodologies of computational rhetoric is this: can we turn a natural language text–with all its rhetorical intricacies–into a computational object?
If we can, then this obliges another question, what kind?
The issue can be framed in terms of data structures, namely, what kind of data structure does a natural language text offer? If a computer is to read it, then that text must offer some form data structure.
So what is the best fit?
My first impulse is to say that a graph is the best data structure for a natural language text.
If this is true, then this theory will a great deal to affirm post-structuralist theories of language as well as challenge existing models.