The rapid advancement of Web2.0 technologies has made social networking sites, such as Facebook and twitter, important venues for individuals to seek and share information. As understanding the information needs of users is crucial for designing and developing tools to support their social Q&A behaviors, in this paper, we present a new way of classifying questions from a design perspective, with the aim of facilitating the development of question routing systems according to individual's information need. As an attempt to understand the questioner's intent in social question and answering environments, we propose a taxonomy of questions posted on Twitter, called ASK. Our taxonomy uncovers three different kinds of questions: accuracy, social, and knowledge. In addition, to enable automatic detection on these three types of information needs, we measured and reported on the differences in ASK types of questions reflected at both lexical and syntactic levels. Copyright is held by the author/owner(s).