Who contributes what?
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2020-09
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Mcode
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Language
en
Pages
14
Series
Information Processing and Management, Volume 57, issue 5
Abstract
Studies of knowledge communities have focused predominantly on contributors who ask questions and/or post replies, while little research has examined the contributions of those who neither pose questions nor suggest answers in knowledge communities. To illuminate member contributions of various sorts, this study evaluated user contribution to knowledge community from three dimensions (influence, content-contribution, and activeness) of immersion. Based on the user activity data of more than 4 million users from Zhihu, the largest online knowledge community in China, we calculated the immersion level for the four user groups (Lurkers, Questioners, Answerers, and Questioner-Answerers) in line with their question-asking and question-answering behaviors in Zhihu. The research findings revealed that Lurkers (members who posted nothing) showed higher community-immersion score than Questioners who asked questions only. The latter, Questioners, had the lowest community-immersion score, while Questioner-Answerers, whoposted both questions and answers, exhibited the greatest contribution in the case knowledge community. We further made horizontal comparison of immersion score among the four different user groups, and found that when immersion scores of the four different user groups are above a certain threshold, the immersion scores of the four different user groups display a consistent distinguishing pattern. This result highlights the similarity of tendencies in behavioral orientation among different users in knowledge communities. Theoretical contributions and practical implications to be gleaned from this research are discussed.Description
Keywords
Contribution, Immersion score, Knowledge community, SQA community, User engagement
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Citation
Deng , S , Jiang , Y , Li , H & Liu , Y 2020 , ' Who contributes what? Scrutinizing the activity data of 4.2 million Zhihu users via immersion scores ' , Information Processing and Management , vol. 57 , no. 5 , 102274 . https://doi.org/10.1016/j.ipm.2020.102274