I'm interested in whether it is possible to classify texts by authorship using just syntactic/grammatical information.
Let's take ten people and have them write three texts. About their favorite hobby, a political commentary and the third one is a fictional story. For the classification I do not want to use information like vocabulary or typos but just the grammatical role of a word in a sentence.
Is it possible to turn such information into a vector f.x. and classify it?
As suggested by hippietrail I'll try to clarify further what aspect I am interested in.
Naturally one can quantify anything and then have a clustering or classification algorithm work on it.
Basically you can use any metric you can think up beside just vocab, word frequency and typos. The latter won't even apply to identifying edited texts. Things like collocations, hyphenation, sentence length - anything imaginable. (hippietrail)
(hyphenation f.x. does not interest me for the purposes of this question - only the grammatical level.)
But I am not a linguist and I wouldn't want to start from scratch guessing my way to a useful quantification. So I am wondering whether there is already a quantification/vectorization of the above mentioned grammatical information distilled from a text that is known to serve this purpose of authorship identification sufficiently well. Maybe even a "classical" approach.