PANcakes Team: A Composite System of Domain-Agnostic Features For Author Profiling
نویسندگان
چکیده
We present the system we built for participating in the PAN-2016 Author Profiling Task [9]. The task asked to predict the gender and the age group of a person given several samples of his/her writing, and it was offered for three different languages: English, Spanish, and Dutch. We participated in both subtasks, for all three languages. Our approach focused on extracting genre-agnostic features such as bag-of-words, sentiment and topic derivation, and stylistic features. We then used these features to train SVM-based classifiers, as implemented in LIBLINEAR for the gender classification sub-task, and in LIBSVM for the age classification sub-task.
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