TY - GEN
T1 - Reinventing the wheel
T2 - 40th International Conference on Information Systems, ICIS 2019
AU - Liu, Xiaohui
AU - Liu, Fei
AU - Li, Yijing
AU - Cai, Zhao
AU - Lim, Eric T.K.
N1 - Funding Information:
Work in this paper was supported by the National Natural Science Foundation of China (NSFC: 71801204)
Publisher Copyright:
© 40th International Conference on Information Systems, ICIS 2019. All rights reserved.
PY - 2019/12
Y1 - 2019/12
N2 - Duplicate questions are common occurrences in Question Answering Communities (QACs) and impede the development of efficacious problem-solving communities. Yet, there is a dearth of research that has sought to shed light on the mechanisms underlying question duplication. Building on the information adoption model, we advance a research model that posits information quality and source credibility as factors deterring users from asking redundant questions within QACs. Furthermore, considering the question-answer dichotomy intrinsic to QACs, we distinguish the quality and credibility of questions from those of answers as distinctive inhibitors of question duplication. We empirically validate our hypotheses on a leading QAC platform by harnessing a deep learning algorithm to detect duplications on over 9,380,000 question pairs. Results revealed that while the credibility of both questions and answers could alleviate question duplication, visual and actionable elements are more effective in preventing question duplication by boosting the quality of questions and answers respectively.
AB - Duplicate questions are common occurrences in Question Answering Communities (QACs) and impede the development of efficacious problem-solving communities. Yet, there is a dearth of research that has sought to shed light on the mechanisms underlying question duplication. Building on the information adoption model, we advance a research model that posits information quality and source credibility as factors deterring users from asking redundant questions within QACs. Furthermore, considering the question-answer dichotomy intrinsic to QACs, we distinguish the quality and credibility of questions from those of answers as distinctive inhibitors of question duplication. We empirically validate our hypotheses on a leading QAC platform by harnessing a deep learning algorithm to detect duplications on over 9,380,000 question pairs. Results revealed that while the credibility of both questions and answers could alleviate question duplication, visual and actionable elements are more effective in preventing question duplication by boosting the quality of questions and answers respectively.
KW - Information Adoption
KW - Question Duplication
KW - Question-Answering
UR - http://www.scopus.com/inward/record.url?scp=85114902420&partnerID=8YFLogxK
M3 - Conference article published in proceeding or book
AN - SCOPUS:85114902420
T3 - 40th International Conference on Information Systems, ICIS 2019
BT - 40th International Conference on Information Systems, ICIS 2019
PB - Association for Information Systems
Y2 - 15 December 2019 through 18 December 2019
ER -