A Random Forest Approach for Authorship Profiling
Alonso Palomino-Garibay, Adolfo T. Camacho-González, Ricardo A. Fierro-Villaneda, Irazú Hernández-Farías, Davide Buscaldi, Iván Meza · Cross-Language Evaluation Forum · 2015
In this paper we present our approach to extract profile information from anonymized tweets for the author profiling task at PAN 2015 ( 10). Particularly we explore the versatility of random forest classifiers for the genre and age groups information and random forest regressions to score important aspects of the personality of a user. Furthermore we propose a set of features tailored for this task based on characteristics of the twitters. In particular, our approach relies on previous proposed features for sentiment analysis tasks.