  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. To the best of our
knowledge, this is the first such analysis of its kind on this important topic.
We also use a sparse nonnegative matrix factorization technique to
automatically induce interpretable semantic factors from the question dataset.
We also document various patterns on response prediction we observe during our
analysis in the data. For instance, we found that preference-probing questions
are scantily answered. Our method is robust to capture such latent response
factors. We hope to make our code and datasets publicly available upon
publication of the paper.
