International Journal of Crowd Science 2019, 3(3): 348-372 https://doi.org/10.1108/IJCS-03-2019-0011

Research paper |

Open Access | Issue | Published: 09 December 2019

Expert recommendation in community question answering: a review and future direction

Show Author's Information Hide Author's Information Zhengfa Yang^¹(

), Qian Liu^², Baowen Sun^¹, Xin Zhao^³

Central University of Finance and Economics, Beijing, China

China Center for Internet Economy Research, Central University of Finance and Economics, Beijing, China

School of Economics and Management, Xi’an University of Technology, Xi’an, China

Keywords:

Community question answering, Knowledge sharing, Expert finding, Expert recommendation

Cite this article:

Yang Z, Liu Q, Sun B, et al. Expert recommendation in community question answering: a review and future direction. International Journal of Crowd Science, 2019, 3(3): 348-372. https://doi.org/10.1108/IJCS-03-2019-0011

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Abstract Full text About this article

Abstract

Purpose

This paper aims to make it convenient for those who have only just begun their research into Community Question Answering (CQA) expert recommendation, and for those who are already concerned with this issue, to ease the extension of our understanding with future research.

Design/methodology/approach

In this paper, keywords such as “CQA”, “Social Question Answering”, “expert recommendation”, “question routing” and “expert finding” are used to search major digital libraries. The final sample includes a list of 83 relevant articles authored in academia as well as industry that have been published from January 1, 2008 to March 1, 2019.

Findings

This study proposes a comprehensive framework to categorize extant studies into three broad areas of CQA expert recommendation research: understanding profile modeling, recommendation approaches and recommendation system impacts.

Originality/value

This paper focuses on discussing and sorting out the key research issues from these three research genres. Finally, it was found that conflicting and contradictory research results and research gaps in the existing research, and then put forward the urgent research topics.

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Abstract

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About this article

Expert recommendation in community question answering: a review and future direction

Show Author's information Hide Author's Information Zhengfa Yang^¹(

), Qian Liu^², Baowen Sun^¹, Xin Zhao^³

Central University of Finance and Economics, Beijing, China

China Center for Internet Economy Research, Central University of Finance and Economics, Beijing, China

School of Economics and Management, Xi’an University of Technology, Xi’an, China

Abstract

Purpose

Design/methodology/approach

Findings

Originality/value

Keywords: Community question answering, Knowledge sharing, Expert finding, Expert recommendation

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Received: 21 March 2019

Revised: 12 October 2019

Accepted: 16 October 2019

Published: 09 December 2019

Issue date: December 2019

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Zhengfa Yang, Qian Liu, Baowen Sun and Xin Zhao. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode