Roy, Pradeep Kumar, Saumya, Sunil, Singh, Jyoti Prakash et al. (2 more authors) (2023) Analysis of community question‐answering issues via machine learning and deep learning:State‐of‐the‐art review. CAAI Transactions on Intelligence Technology. pp. 95-117. ISSN 2468-2322
Abstract
Over the last couple of decades, community question-answering sites (CQAs) have been a topic of much academic interest. Scholars have often leveraged traditional machine learning (ML) and deep learning (DL) to explore the ever-growing volume of content that CQAs engender. To clarify the current state of the CQA literature that has used ML and DL, this paper reports a systematic literature review. The goal is to summarise and synthesise the major themes of CQA research related to (i) questions, (ii) answers and (iii) users. The final review included 133 articles. Dominant research themes include question quality, answer quality, and expert identification. In terms of dataset, some of the most widely studied platforms include Yahoo! Answers, Stack Exchange and Stack Overflow. The scope of most articles was confined to just one platform with few cross-platform investigations. Articles with ML outnumber those with DL. Nonetheless, the use of DL in CQA research is on an upward trajectory. A number of research directions are proposed.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022The Authors. |
Keywords: | answer quality,community question answering,deep learning,expert user,Machine Learning,question quality |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > The York Management School |
Depositing User: | Pure (York) |
Date Deposited: | 06 May 2022 12:00 |
Last Modified: | 08 Mar 2025 00:09 |
Published Version: | https://doi.org/10.1049/cit2.12081 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1049/cit2.12081 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:186545 |
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Description: CAAI Trans on Intel Tech - 2022 - Roy - Analysis of community question‐answering issues via machine learning and deep
Licence: CC-BY 2.5