articleMay 8, 2007Closed access

Expertise networks in online communities

University of Michigan–Ann Arbor

Indexed incrossref

Abstract

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…

Citation impact

793
total citations
FWCI
121.77
Percentile
100%
References
29
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • PageRank
  • Java
  • Ranking (information retrieval)
  • Set (abstract data type)
  • World Wide Web
  • Social network (sociolinguistics)
  • Data science
No related works found for this paper.

Funding