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Early prediction of promising expert users on community question answering sites

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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.

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Notes

  1. https://archive.org/details/stackexchange.

  2. https://scikit-learn.org/stable/modules/sgd.html.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Information Technology, Surat, Gujarat, India

    Pradeep Kumar Roy

  2. Department of Computer Science and Engineering, National Institute of Technology Patna, Patna, India

    Jyoti Prakash Singh

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  1. Pradeep Kumar Roy
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  2. Jyoti Prakash Singh
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Roy, P.K., Singh, J.P. Early prediction of promising expert users on community question answering sites. Int J Syst Assur Eng Manag (2024). https://doi.org/10.1007/s13198-024-02303-0

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