Author Profiling for English and Spanish Text Notebook for PAN at CLEF 2013

This paper describes an approach for the author profiling task of the PAN 2013 challenge. This work is based on the idea of linguistic modality that has been successfully used in other classification tasks such as authorship attribution. We consider three different modalities: syntactic, stylistic, and semantic, each representing a different aspect of text. For each modality, we extract informative meta features by computing the similarity relations between the feature vectors in the test files and the centroids of modality specific clusters. Since we were provided texts in both Spanish and English, we build a language independent framework for author profiling. For both English and Spanish documents, our system performed well for the age identification task. For gender prediction, although our system could not perform as expected for English, it yielded good results on Spanish.