Examining Multiple Features for Author Profiling
Edson R. D. Weren, Anderson Uilian Kauer, Lucas Eishi Pimentel Mizusaki, Viviane P. Moreira, José Palazzo Moreira de Oliveira, Leandro Krug Wives · Cadernos de Linguística e Teoria da Literatura (Universidade Federal de Minas Gerais) · 2014
Authorship analysis aims at classifying texts based on the stylistic choices of their authors. The idea is to discover characteristics of the authors of the texts. This task has a growing importance in forensics, security, and marketing. In this work, we focus on discovering age and gender from blog authors. With this goal in mind, we analyzed a large number of features -- ranging from Information Retrieval to Sentiment Analysis. This paper reports on the usefulness of these features. Experiments on a corpus of over 236K blogs show that a classifier using the features explored here have outperformed the state-of-the art. More importantly, the experiments show that the Information Retrieval features proposed in our work are the most discriminative and yield the best class predictions.