Author Profiling: Age Prediction Based on Advanced Bayesian Networks

In this study, we present a new method for profiling the author of an anonymous English text. The aim of author profiling is to determine demographic (age, gender, region, education level) and psychological (personality, mental health) properties of the authors of a text, especially authors of user generated content in social media. To obtain the best classification, authors resort to machine learning methods. Focusing on the works which use the Bayesian networks, all those methods rather apply the Bayesian naïve classifiers which do not yield the best results. Therfore we propose a method based on advanced Bayesian networks for age prediction to over come the mentioned detail problem. We obtained promising results by relying on an English PAN@CLEF 2013 corpus. The obtained results are comparable to the ones obtained by the best state of the art methods. The software and data can be publicly downloaded from www.cicling.org/2016/ data/248/CICLING_248.zip.