  TurboTax AnswerXchange is a social Q&A system supporting users working on
federal and state tax returns. Using 2015 data, we demonstrate that content
popularity (or number of views per AnswerXchange question) can be predicted
with reasonable accuracy based on attributes of the question alone. We also
employ probabilistic topic analysis and uplift modeling to identify question
features with the highest impact on popularity. We demonstrate that content
popularity is driven by behavioral attributes of AnswerXchange users and
depends on complex interactions between search ranking algorithms,
psycholinguistic factors and question writing style. Our findings provide a
rationale for employing popularity predictions to guide the users into
formulating better questions and editing the existing ones. For example,
starting question title with a question word or adding details to the question
increase number of views per question. Similar approach can be applied to
promoting AnswerXchange content indexed by Google to drive organic traffic to
TurboTax.
