The irreplaceable key to the triumph of Question & Answer (Q&A) platforms is
their users providing high-quality answers to the challenging questions posted
across various topics of interest. Recently, the expert finding problem
attracted much attention in information retrieval research. In this work, we
inspect the feasibility of supervised learning model to identify data science
experts in Reddit. Our method is based on the manual coding results where two
data science experts labelled expert, non-expert and out-of-scope comments. We
present a semi-supervised approach using the activity behaviour of every user,
including Natural Language Processing (NLP), crowdsourced and user feature
sets. We conclude that the NLP and user feature sets contribute the most to the
better identification of these three classes It means that this method can
generalise well within the domain. Moreover, we present different types of
users, which can be helpful to detect various types of users in the future