Modelling Question Selection Behaviour In Online Communities

Value of online Question Answering (Q&A) communities is driven by the question -answering behaviour of its members. Finding the questions that members are willing to answer is therefore vital to the efficient operation of such communities. In this paper, we aim to identify the parameters that correlate with such behaviours. We train different models and construct effective predictions using various user, question and thread feature sets. We show that answering behaviour can be predicted with a high level of success.