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Using Topic Analysis to Compute Identity Group Attributes

  • Lashon B. Booker
  • Gary W. Strong
Conference paper

Abstract

Preliminary experiments are described on modeling social group phenomena that appear to address limitations of social network analysis. Attributes that describe groups independently of any specific members are derived from publication data in a field of science. These attributes appear to explain observed phenomena of group effects on individual behavior without the need for the individual to have a network relationship to any member of the group. The implications of theseresults are discussed.

Keywords

Social Network Analysis Identity Group Latent Dirichlet Allocation Individual Document Latent Dirichlet Allocation Model 
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 Science+Business Media, LLC 2008

Authors and Affiliations

  • Lashon B. Booker
    • 1
  • Gary W. Strong
    • 2
  1. 1.The MITRE CorporationMcLeanVirginia
  2. 2.Human Language Technology Center of Excellence JohnsHopkins UniversityBaltimore

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