document: Expertise networks in online communities : structure and algorithms 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 .
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