PAN at FIRE: Overview of the PR-SOCO Track on Personality Recognition in SOurce COde
نویسندگان
چکیده
Author profiling consists of predicting some author’s characteristics (e.g. age, gender, personality) from her writing. After addressing at PAN@CLEF mainly age and gender identification, and also personality recognition in Twitter, in this PAN@FIRE track on Personality Recognition from SOurce COde (PR-SOCO) we have addressed the problem of predicting author’s personality traits from her source code. In this paper, we analyse 48 runs sent by 11 participant teams. Given a set of source codes written in Java by students who answered also a personality test, participants had to predict personality traits, based on the big five model. Results have been evaluated with two complementary measures (RMSE and Pearson product-moment correlation) that have permitted to identify whether systems with low error rates may work due to random chance. No matter the approach, openness to experience is the trait where the participants obtained the best results for both measures.
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