Questions form an integral part of our everyday communication, both offline and online. Getting responses to our questions from others is fundamental to satisfying our information need and in extending our knowledge boundaries. A question may be represented using various factors such as social, syntactic, semantic, etc. We hypothesize that these factors contribute with varying degrees towards getting responses from others for a given question. We perform a thorough empirical study to measure effects of these factors using a novel question and answer dataset from the website Reddit.com. We also use a sparse non-negative matrix factorization technique to automatically induce interpretable semantic factors from the question dataset. Such interpretable factor-based analysis overcomes limitations faced by prior related research. We also document various patterns on response prediction we observe during our analysis. For instance, we found that preference-probing questions are rarely answered by actors.