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CIKM
2010
Springer

Expert identification in community question answering: exploring question selection bias

8 years 9 months ago
Expert identification in community question answering: exploring question selection bias
Community Question Answering (CQA) services enables users to ask and answer questions. In these communities, there are typically a small number of experts amongst the large population of users. We study which questions a user select for answering and show that experts prefer answering questions where they have a higher chance of making a valuable contribution. We term this preferential selection as question selection bias and propose a mathematical model to estimate it. Our results show that using Gaussian classification models we can effectively distinguish experts from ordinary users over their selection biases. In order to estimate these biases, only a small amount of data per user is required, which makes an early identification of expertise a possibility. Further, our study of bias evolution reveals that they do not show significant changes over time indicating that they emanates from the intrinsic characteristics of users. Categories and Subject Descriptors
Aditya Pal, Joseph A. Konstan
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where CIKM
Authors Aditya Pal, Joseph A. Konstan
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