Paper Title
Gender and Age Classification on the Basis of Blogs

Abstract
Text is still the most prevalent Internet media type. Examples of this include popular social networking applications such as Twitter, Craigslist, Facebook, etc. Other web applications such as e-mail, blog, chat rooms, etc. are also mostly text based. A question we address in this paper that deals with text based Internet forensics is the following: given a short text document, can we identify if the author is a man or a woman? This question is motivated by recent events where people faked their gender on the Internet. Note that this is different from the authorship attribution problem. Analysis of a corpus of tens of thousands of blogs indicates significant differences in writing style and content between male and female bloggers as well as among authors of different ages. Such differences can be exploited to determine an unknown authorís age and gender on the basis of a blogís vocabulary. Keywords- Blogs, Support Vector Machine, corpus, information retrieval