Author Profiling for Arabic Tweets based on n-grams

This paper presents an approach for author profiling of an unknown users from their texts produced in social media. In particular, we address the identification of two profile dimensions: gender and language variety, of Arabic twitter users based on their tweets. Our approach focused on applying metaclassification technique on features extracted from tweets body. We explored two main sets of features which are character and word n-grams. The proposed approach allowed us to reach promising results for both language variety and gender identification