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Dynamic Networks: Rapid Assessment of Changing Scenarios

  • Nadya Belov
  • Michael K. Martin
  • Jeff Patti
  • Jeff Reminga
  • Angela Pawlowski
  • Kathleen M. Carley
Conference paper

As events unfold, the underlying networks change. Most network science tools, however, assume analysts have a single snapshot of the data, or at most, a second snapshot at a different time. The underlying network representation schemes, assessment technologies, and visualizations do not lend themselves naturally to dynamic networks. Herein, we identify key criteria for network representation of dynamic, uncertain information and present a technology enabler that combines information fusion and dynamic network analysis. The value of technological solutions for network analytics in a dynamic environment are discussed.

Keywords

Dynamic Network Data Fusion Boundary Spanner Software Research Human Network 
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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References

  1. 1.
    Carley K, Columbus D, DeReno M, Reminga J, Moon I (2008) ORA User's Guide 2008. Technical Report, Carnegie Mellon University, School of Computer Science, Institute for Software Research, CMU-ISR-08-125.Google Scholar
  2. 2.
    Borgatti S, Everett M, Freeman L (1999) UCINET 5 for Windows: Software for Social Network Analysis. Analytic Technologies, Inc., Natick, MA.Google Scholar
  3. 3.
    Brandes U, Eiglsperger M, Herman I, Himsolt M, and Marshall M.S (2002) GraphML Progress Report: Structural Layer Proposal, Proceedings of the 9th International Symposium on Graph Drawing, Lecture Notes of Computer Science, Volume 2265, pp. 501–512.Google Scholar
  4. 4.
    Tsvetovat M, Reminga J, Carley K (2004) DyNetML: Interchange Format for Rich Social Network Data. CASOS Technical Report. Carnegie Mellon University, School of Computer Science, Institute for Software Research International, CMU-ISRI-04-105.Google Scholar
  5. 5.
    Nick Morizio (2008) Context Selection for Linguistic Data Fusion, in the Proceedings of the 11th International Conference on Information Fusion, Cologne, Germany, June 30-July 3, 2008.Google Scholar
  6. 6.
    Schreiber C, Carley K (2004) Construct – A Multi-agent Network Model for the Co-evolution of Agents and Socio-cultural Environments. Construct – A Multi-agent Network Model for the Co-evolution of Agents and Socio-cultural Environments. Technical Report, Carnegie Mellon University, School of Computer Science, Institute for Software Research International, CMU-ISRI-04-109.Google Scholar
  7. 7.
    McCulloh I, Carley K (2008a) Social Network Change Detection. Technical Report, Carnegie Mellon University, School of Computer Science, Institute for Software Research, CMU-ISR-08-116.Google Scholar
  8. 8.
    McCulloh I, Carley K (2008b) Detecting Change in Human Social Behavior Simulation. Technical Report, Carnegie Mellon University, School of Computer Science, Institute for Software Research, CMU-ISR-08-135.Google Scholar
  9. 9.
    Moon I, Carley K (2007) Modeling and Simulation of Terrorist Networks in Social and Geospatial Dimensions. IEEE Intelligent Systems, Special issue on Special issue on Social Computing – Sep/Oct '07, 22, 40–49.Google Scholar

Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  1. 1.Lockheed Martin Advanced Technology LaboratoriesCherry HillNew Jersey
  2. 2.Center for Computational Analysis of Social and Organizational Systems, Institute for Software Research,Carnegie Melon UniversityPittsburghPennsylvania

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