Predicting the author’s gender using computational stylistic methods

Online textual production increases rapidly through Web 2.0 media, enriching traditional text genres with new ones. Blogs produce daily more than 900,000 posts, while in microblogging services like Twitter, approximately 5,700 tweets per second are sent from more than 231 million registered accounts. Automatic identification of author’s characteristics (e.g. gender, age and personality) in such micro-texts have started to be the focus of intensive research, mainly due to the many possible applications including forensics, online audience identification for targeted advertisement and socio(linguistic) analysis on gender identity issues.