Content

Knowledge-iN

A Study of Knowledge Sharing Online Community

Kevin Nam, Mark Ackerman, Lada A. AdamicPublication (CHI’09)

Keywords: collective intelligence, knowledge building community, online question-answering, user information behavior, data mining, user interaction

Large general-purposed community question-answering sites are becoming popular as a new venue for generating knowl edge and helping users in their information needs.  In this paper we analyze the characteristics of knowledge genera tion and user participation behavior in the largest question-answering online community in South Korea, Naver Know ledge.iN.  We collected and analyzed over 2.6 million ques tion/answer pairs from fifteen categories between 2002 and 2007, and have interviewed twenty six users to gain insights into their motivations, roles, usage and expertise.  We find altruism, learning, and competency are frequent motivations for top answerers to participate, but that participation is often highly intermittent.  Using a simple measure of user perfor mance, we find that higher levels of participation correlate with better performance.  We also observe that users are mo tivated in part through a point system to build a comprehen sive knowledge database. These and other insights have sig nificant implications for future knowledge generating online communities.

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