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Extracting Social Networks Enriched by Using Text

  • Mathilde Forestier
  • Julien Velcin
  • Djamel Zighed
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6804)

Abstract

Forums on the Internet are an overwhelming source of knowledge considering the number of topics treated and users who participate in these discussions. This volume of data is difficult to comprehend for a person with respect for the large number of posts. Our work proposes a new formal framework for synthesizing information contained in these forums. We extract a social network that reflects reality by extracting multiple relationships between individuals (structural relationship, name and text quotation relationships). These relationships are created from the structure and the content of the discussion. Results show that discovering quotation relationships from forums is not trivial.

Keywords

Social Network Structural Relationship Quotation Mark Egocentric Network Implicit Relationship 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mathilde Forestier
    • 1
  • Julien Velcin
    • 1
  • Djamel Zighed
    • 1
  1. 1.ERIC LaboratoryUniversity of Lyon 2France

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