XRCE Personal Language Analytics Engine for Multilingual Author Profiling: Notebook for PAN at CLEF 2015

This technical notebook describes the methodology used - and results achieved - for the PAN 2015 Author Profiling Challenge by the team from Xe- rox Research Centre Europe (XRCE). This year, personality traits are introduced alongside age and gender in a corpus of tweets in four languages - English, Span- ish, Italian and Dutch. We describe a largely language agnostic methodology for classification which uses language specific linguistic processing to generate fea- tures. We also report on experiments in which we use machine translation to accommodate for languages in which there is less training data. Native language results are successful, but socio-demographic signals in language seem to be lost under MT conditions.

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