Combining social network analysis with semantic relations to support the evolution of a scientific community

  • Authors:
  • Andreas Harrer;Nils Malzahn;Sam Zeini;H. Ulrich Hoppe

  • Affiliations:
  • University of Duisburg-Essen;University of Duisburg-Essen;University of Duisburg-Essen;University of Duisburg-Essen

  • Venue:
  • CSCL'07 Proceedings of the 8th iternational conference on Computer supported collaborative learning
  • Year:
  • 2007

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Abstract

This paper presents an analytical approach to support organisational learning in terms of the evolution of a scientific community based on a combination of social network analysis and semantic relations. The primary and direct target of the method is to infer hidden or desirable links between subgroups in a networked community. The data source for these inferences comprises memberships in teams and thematic subgroups. The approach has been applied in a case study to a large scientific network on technology enhanced learning.