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 e cient operation of such communities. In this paper, we aim to identify the parameters that correlate with such behaviours. We train di↵erent models and construct e↵ective predictions using various user, question and thread feature sets. We show that answering behaviour can be predicted with a high level of success.