SISN: a toolkit for augmenting expertise sharing via social networks

  • Authors:
  • Jun Zhang;Yang Ye;Mark S. Ackerman;Yan Qu

  • Affiliations:
  • School of Information, University of Michigan;Department of Linguistics, University of Michigan;EECS and School of Information, University of Michigan;College of Information Studies, University of Maryland

  • Venue:
  • OCSC'07 Proceedings of the 2nd international conference on Online communities and social computing
  • Year:
  • 2007

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Abstract

The current study attempts to address the social-technical gap by developing a toolkit that can help information seekers to search for expertise and seek information via their social networks. The focus of the current study is technical development of a toolkit that supports expertise sharing via social networks. Once such a toolkit is in place, it can facilitate researches that are more concerned with applications in social and organizational perspectives. Following a proposed full-fledged social network-powered expert searching and information sharing framework on the theoretical side, the study then reports a toolkit of Seeking Information via Social Networks (SISN), which is a general-purpose toolkit for social network-based information sharing applications that combines techniques in information retrieval, social network, and peer-to-peer system.