Early prediction of promising expert users on community question answering sites

Pradeep Kumar Roy () and Jyoti Prakash Singh ()
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Pradeep Kumar Roy: Indian Institute of Information Technology
Jyoti Prakash Singh: National Institute of Technology Patna

International Journal of System Assurance Engineering and Management, 2024, vol. 15, issue 7, No 7, 2902-2913

Abstract: Abstract Community question answering (CQA) sites have become a popular medium for exchanging knowledge with other members of the community. Users can publish questions, answers, and comments on these sites. Furthermore, users of the CQA sites are able to express their thoughts on a post by voting positively or negatively. People anticipate rapid and high-quality answers from these CQA sites, which are often provided by a small group of users known as experts. A large number of queries remain unanswered on these forums, emphasising the scarcity of experts. To address this problem, we presented a methodology for predicting promising expert users for CQA sites. Promising experts are individuals that have just joined the community and have shown glimpses of producing high-quality content to the site. The suggested method looks at the first month of a user’s postings to determine whether or not the individual is a promising expert. The experimental findings revealed that the suggested approach accurately predicts future experts.

Keywords: Community question answering; Expert users; Question routing; Classification; Machine learning (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13198-024-02303-0

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