Recent research has indicated that social networking sites are being adopted as venues for online information-seeking. In order to understand questioner’s intention in social Q&A environments and to better facilitate such behaviors, we define two types of questions: subjective information-seeking questions and objective information seeking ones. To enable automatic detection on question subjectivity, we propose a predictive model that can accurately distinguish between the two classes of questions. By applying the classifier on a larger dataset, we present a comprehensive analysis to compare questions with subjective and objective orientations, in terms of their length, response speed, as well as the characteristics of their respondents. We find that the two types of questions exhibited very different characteristics. Also, we noticed that question subjectivity plays a significant role in attracting responses from strangers. Our results validate the expected benefits of differentiating questions according to their subjectivity orientations, and provide valuable insights for future design and development of tools that can assist the information seeking process under social context.