Author Profiling Using Style-based Features Notebook for PAN at CLEF 2013

Abstract. In this paper, we present a method for profiling the author of an anonymous text. Our approach is based on learning the author profile with a focus on dimensions age and gender. Our system takes as input a document which is written in English or in Spanish and generates the age and the gender of its author. First, we computed a ranked list of words that occur in the corpus and we grouped them into classes according to their similarities. Then, we calculated the TF * IDF score of each class for each document in order to find the stylistic differences between men and women, on the one hand, and those between different age intervals on the other hand. After that, we applied the learning process on 66 % of the English and the Spanish corpuses using decision trees through the J48 algorithm. In factwe got the second place in the competition for the English corpus;Our system has shown a high level of accuracy and effectiveness in treating the gender dimension and we got the best accuracy for the entire PAN 2013 competition. Keywords.Machine learning, Author profiling, Style-based features, Decision trees