User generated text on social media sites is a rich source of information that can be used to identify different aspects of their authors. Proper mining of this content provides an automatic way of identifying users which is very valuable for applications that rely on personalisation. In this work, we describe the properties of our multilingual software submitted for PAN2015 which recognizes the age, gender and personality traits of Twitter users in four languages, namely, English, Spanish, Dutch and Italian
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