<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lada A. Adamic</style></author><author><style face="normal" font="default" size="100%">Zhang, Jun</style></author><author><style face="normal" font="default" size="100%">Bakshy, Eytan</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Knowledge Sharing and Yahoo Answers: Everyone Knows Something</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 17th International Conference on World Wide Web</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">expertise finding</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">help seeking</style></keyword><keyword><style  face="normal" font="default" size="100%">knowledge sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">online communities</style></keyword><keyword><style  face="normal" font="default" size="100%">Q&amp;A communities</style></keyword><keyword><style  face="normal" font="default" size="100%">QA communities</style></keyword><keyword><style  face="normal" font="default" size="100%">question answering</style></keyword><keyword><style  face="normal" font="default" size="100%">social network analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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&#039;s curiosity about a countless number of things. In this paper, we seek to understand YA&#039;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&#039; 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.&lt;/p&gt;</style></abstract></record></records></xml>