Finding experts in community-based question-answering services
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Various methods have been proposed to help find answerers for a question in QA communities, but almost all work heavily depends on users' QA history. In this paper we seek to investigate the feasibility of leveraging users' non-QA social activities as a way of gaining insight into their question answering behavior. We collected data of 4,484 users on a QA community in an enterprise and examined the relationship of their QA behaviors and non-QA activities supported by other social tools. We found that the two sets of behavioral indicators are significantly correlated. The top user group for non-QA activities outperformed lower groups in both number and quality of the answers. Regression analysis showed involvement in personal blog, micro-blog and forum and replying and recommending behaviors in non-QA communities were predictive of a user's likelihood of answering questions. Online observations provided a qualitative understanding. Design implications and future work were discussed.