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Burel, Gregoire; He, Yulan; Mulholland, Paul and Alani, Harith
(2015).
DOI: https://doi.org/10.1145/2740908.2745935
URL: http://dl.acm.org/citation.cfm?id=2745935
Abstract
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 cor- relate 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.
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About
- Item ORO ID
- 44014
- Item Type
- Conference or Workshop Item
- ISBN
- 1-4503-3473-3, 978-1-4503-3473-0
- Keywords
- social Q&A platforms; online communities; user behaviour; social media
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Centre for Research in Computing (CRC)
- Copyright Holders
- © 2015 The Authors
- Related URLs
- Depositing User
- Kay Dave