Seeking and Offering Expertise Across Categories: A Sustainable Mechanism Works for Baidu Knows

Authors

  • Jiang Yang University of Michigan
  • Xiao Wei University of Michigan

Keywords:

Baidu Knows, Knowledge Sharing, QA site, User Behavior, Incentive

Abstract

This paper presents the first comprehensive exploration of the largest Chinese online knowledge sharing community-Baidu Knows. With analyzing 5.2 millions questions and 2.7 million users participated during 4.5 months on the site in 2008, we investigate how users adjust initial attempts and behave differently according to the level of participation; in particular, there is a positive dynamic for answerers to input more, be more focused, win more, and thus be rewarded more. As the result, a core user group forms to actively participate in both asking and answering across categories, thus maintaining a self-sufficient community. In addition, a prominent "sense of community" would enhance the social bonds within the community, especially for the contributors who can offer expertise but can rarely learn from others. The study suggests Baibu Knows as a successful design instance for further studies.

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Published

2009-03-19

How to Cite

Yang, J., & Wei, X. (2009). Seeking and Offering Expertise Across Categories: A Sustainable Mechanism Works for Baidu Knows. Proceedings of the International AAAI Conference on Web and Social Media, 3(1), 162-169. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/13942