Overview of the RUSProfiling PAN at FIRE Track on Cross-genre Gender Identification in Russian

Tatiana Litvinova, Francisco M. Rangel Pardo, Paolo Rosso, Pavel Seredin, Olga Litvinova
2017 Forum for Information Retrieval Evaluation  
Author profiling consists of predicting some author's traits (e.g. age, gender, personality) from her writing. After addressing at PAN@CLEF 1 mainly age and gender identification, in this RusProfiling PAN@FIRE track we have addressed the problem of predicting author's gender in Russian from a cross-genre perspective: given a training set on Twitter, the systems have been evaluated on five different genres (essays, Facebook, Twitter, reviews and texts where the authors imitated the other gender,
more » ... where the users change their idiostyle). In this paper, we analyse the 22 runs sent by 5 participant teams. The best results (although also the most sparse ones) have been obtained on Facebook.
dblp:conf/fire/LitvinovaPRSL17 fatcat:2c2bfpn6wrh4lgm6hjxehvm2pm