Seeking and Offering Expertise across Categories: A Sustainable Mechanism Works for Baidu Knows
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.
Date: May 17, 2009
Book Title: Int'l AAAI Conference on Weblogs and Social Media
Type: InProceedings
Address: San Jose, CA
Downloads: 129
Has 1 soft copy
remote linkBibtex
@InProceedings{Seeking_and_Offering_Expertise_across_Ca,
author = "Jiang Yang and Xiao Wei",
title = "{Seeking and Offering Expertise across Categories: A Sustainable Mechanism Works for Baidu Knows}",
month = "May",
year = "2009",
address = ", San Jose, CA, ",
booktitle = "Int'l AAAI Conference on Weblogs and Social Media",
}