Simaki, Vasiliki and Aravantinou, Christina and Mporas, Iosif and Megalooikonomou, Vasileios (2015) Using Sociolinguistic Inspired Features for Gender Classification of Web Users. In: Proceedings of the 18th International Conference of Text, Speech and Dialogue. Lecture Notes in Computer Science . Springer, Cham, pp. 587-594. ISBN 9783319240329
Full text not available from this repository.Abstract
In this article we present a methodology for classification of text from web authors, using sociolinguistic inspired text features. The proposed methodology uses a baseline text mining based feature set, which is combined with text features that quantify results from theoretical and sociolinguistic studies. Two combination approaches were evaluated and the evaluation results indicated a significant improvement in both combination cases. For the best performing combination approach the accuracy was 84.36%, in terms of percentage of correctly classified web posts.