TY - CONF T1 - Knowledge Sharing and Yahoo Answers: Everyone Knows Something T2 - Proceedings of the 17th International Conference on World Wide Web Y1 - 2008 A1 - Lada A. Adamic A1 - Zhang, Jun A1 - Bakshy, Eytan A1 - Mark S. Ackerman KW - expertise finding KW - expertise sharing KW - help seeking KW - knowledge sharing KW - online communities KW - Q&A communities KW - QA communities KW - question answering KW - social network analysis AB -

Yahoo Answers (YA) is a large and diverse question-answer forum, acting not only as a medium for sharing technical knowledge, but as a place where one can seek advice, gather opinions, and satisfy one's curiosity about a countless number of things. In this paper, we seek to understand YA's knowledge sharing and activity. We analyze the forum categories and cluster them according to content characteristics and patterns of interaction among the users. While interactions in some categories resemble expertise sharing forums, others incorporate discussion, everyday advice, and support. With such a diversity of categories in which one can participate, we find that some users focus narrowly on specific topics, while others participate across categories. This not only allows us to map related categories, but to characterize the entropy of the users' interests. We find that lower entropy correlates with receiving higher answer ratings, but only for categories where factual expertise is primarily sought after. We combine both user attributes and answer characteristics to predict, within a given category, whether a particular answer will be chosen as the best answer by the asker.

JF - Proceedings of the 17th International Conference on World Wide Web UR - Complete ER - TY - CONF T1 - Expertise networks in online communities: structure and algorithms T2 - Proceedings of the 16th international conference on World Wide Web (WWW'07) Y1 - 2007 A1 - Zhang, Jun A1 - Mark S. Ackerman A1 - Lada A. Adamic KW - expert locators KW - expertise finding KW - help seeking KW - online communities KW - simulation KW - social network analysis AB -

Web-based communities have become important places for people to seek and share expertise. We find that networks in these communities typically differ in their topology from other online networks such as the World Wide Web. Systems targeted to augment web-based communities by automatically identifying users with expertise, for example, need to adapt to the underlying interaction dynamics. In this study, we analyze the Java Forum, a large online help-seeking community, using social network analysis methods. We test a set of network-based ranking algorithms, including PageRank and HITS, on this large size social network in order to identify users with high expertise. We then use simulations to identify a small number of simple simulation rules governing the question-answer dynamic in the network. These simple rules not only replicate the structural characteristics and algorithm performance on the empirically observed Java Forum, but also allow us to evaluate how other algorithms may perform in communities with different characteristics. We believe this approach will be fruitful for practical algorithm design and implementation for online expertise-sharing communities.
 

JF - Proceedings of the 16th international conference on World Wide Web (WWW'07) PB - ACM UR - Complete ER -