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Social Network Analysis and Mining

, Volume 2, Issue 1, pp 69–95 | Cite as

Semantically interconnected social networks

  • Alessandro Cucchiarelli
  • Fulvio D’Antonio
  • Paola Velardi
Review Article

Abstract

Social network analysis aims to identify collaborations and helps people organize themselves through community participation and information sharing. The primary sources for social network modelling are explicit relationships such as co-authoring, citations, friendship, etc. However, to enable the integration of on-line community information and to fully describe the content and structure of community sites, secondary sources of information, such as documents, e-mails, blogs and discussions, can be exploited. In this paper we describe a methodology and a battery of tools to automatically extract from documents the relevant topics shared among community members and to analyse the evolution of the network also in terms of emergence and decay of collaboration themes. Experiments are conducted on a scientific network funded by the European Community, the INTEROP network of excellence, and on the United Kingdom research community in medical image understanding and analysis.

Keywords

Social networks Semantic web Natural language processing Text analysis Clustering Computer-supported collaborative work 

Notes

Acknowledgments

The authors wish to thank Vincenzo Casini for his help in developing the GVI tool.

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Alessandro Cucchiarelli
    • 1
  • Fulvio D’Antonio
    • 1
  • Paola Velardi
    • 2
  1. 1.DIIGAUniversità Politecnica delle MarcheAnconaItaly
  2. 2.DIS‘Sapienza’ University of RomeRomeItaly

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