Author Profiling: Predicting Age and Gender from Blogs Notebook for PAN at CLEF 2013
K. Santosh, Romil Bansal, Mihir Shekhar, Vasudeva Varma · 2013
Abstract Author profiling is the task of determining age, gender, native language or personality type of author by studying their sociolect aspect, that is, how lan-guage is shared by people. In this paper, we propose a Machine Learning ap-proach to determine unknown author’s age and gender. The approach uses three types of features: content based, style based and topic based. We were able to achieve an accuracy of 64.08%, 64.30 % for age and 56.53%, 64.73 % for gender in English and Spanish respectively.