Grammar Checker Features for Author Identification and Author Profiling Notebook for PAN at CLEF 2013

Our work on author identification and author profiling is based on the question: Can the number and the types of grammatical errors serve as indicators for a specific author or a group of people? In order to detect the grammatical errors we base our approach on the output of the open-source library LanguageTool. In the case of the author identification we transform the problem into a statistical test, where an unknown document is written by another author when the distribution of grammatical errors deviated from documents of a reference corpus. For author profiling we implemented an instance based classification approach, namely a k-NN classifier, in combination with a Language Model where a text is assigned to a specific age or gender group where the according reference corpus contains the closest match. In the evaluation we found that for both scenarios grammatical errors do perform better than the baseline and do capture an aspect of a writing style, which is not contained in more traditional features, like stylometric features or word n-grams.