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2013 | 3 | 3 | 53-61

Article title

Analyzing Behavior Within Networks After Fragmentation. The Coagulant Agent Approach

Authors

Title variants

Languages of publication

EN

Abstracts

EN
This paper introduces a simple mathematical algorithm for identifying the nodes that will most likely act as re-coagulants once the ‘key-players’ are removed. By comparing the difference between in-degree and out-degree centrality scores (assuming that the relational data are directed) and comparing that value with the overall degree score, one can infer where a node sits on the ‘sink-source’ continuum. Furthermore, assuming that the nodes will not change their behavior patterns as a result of the prior ‘intervention’, this algorithm could indicate whether the nodes will act as relational ‘magnets’ (will attract new ties) or as ‘leeches’ (will seek to attach themselves to other nodes).

Publisher

Year

Volume

3

Issue

3

Pages

53-61

Physical description

Dates

published
2013-10-01
online
2015-05-06

Contributors

author
  • University of Bucharest Department of Sociology

References

  • Borgatti, S.P. (2003) ‘The Key Player Problem’. In Breiger, R., K. Carley, and P. Pattison (eds.) Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers, pp. 241-252. National Academy of Sciences Press.
  • Borgatti, S.P. (2006) ‘Identifying sets of key players in a network’. Computational, Mathematical and Organizational Theory, 12(1): 21-34.
  • Carley, K. M. (2006) ‘Destabilization of Covert Networks’. Computational and Mathematical Organization Theory, 12(1): 51-66.[Crossref]
  • Carley, K. M., J. Lee and D. Krackhardt (2002) ‘Destabilizing Networks’. Connections, 24(3): 79-92.
  • Carley, K. M., J. Reminga and N. Kamneva (2003) ‘Destabilizing Terrorist Networks’, . Retrived: August 26, 2013.
  • Cooke, R.J.E. (2006) Link Prediction and Link Detection in Sequences of Large Social Networks Using Temporal and Local. Department of Computer Science: University of Cape Town.
  • Everton, S. (2013) Disrupting Dark Networks. Cambridge: Cambridge University Press.
  • Gourley, S., J. C. Bohorquez, A. Dixon, M. Spagat and N. Johnson (2009) ‘Common Ecology Quantifies Human Insurgency’. Nature 462(15): 911-914.[WoS]
  • Keegan, B., M.A. Ahmed, D. Williams, J. Srivastava and N. Contractor (2010) ‘Dark Gold: Statistical Properties of Clandestine Networks in Massively Multiplayer Online Games’, . Retrieved: August 26, 2013.
  • Kim, H., J. Tang, R. Anderson and C. Mascolo (2012) ‘Centrality Prediction in Dynamic Human Contact Networks’. Compute, 56(3): 983-996.
  • Krebs, V. (2002) ‘Mapping Networks of Terrorist Cells’. Connections, 24(3): 43-52.
  • Morselli, C. (2009) Inside Criminal Networks. New York: Springer.
  • Raab, J. and B. Milward (2003) ‘Dark Networks as Problems’. Journal of Public Administration Research and Theory, 13(4): 413-439.[Crossref]
  • Robins, G. and Y. Kashima (2008) ‘Social Psychology and Social Networks: Individuals and Social Systems’. Asian Journal of Social Psychology, 1: 1–12.[WoS]
  • Robins, G. (2009) ‘Understanding Individual Behaviors Within Covert Networks: The Interplay of Individual Qualities, Psychological Predispositions, and Network Effects in Trends’, . (Retrieved: August 26, 2013).
  • Sageman, M. (2004) ‘Statement to the National Commission on Terrorist Attacks Upon the United States’, . (Retrieved: August 26,2013).
  • Sageman, M. (2004) Understanding Terror Networks. Philadelphia: University of Pennsylvania Press.
  • Sageman, M. (2008) Leaderless Jihad: Terror Networks in the Twenty-First Century. Philadelphia: University of Pennsylvania Press.
  • Tsvetovat, M. and K.M. Carley (2005) ‘Structural Knowledge and Success of Anti-Terrorist Activity: The Downside of Structural Equivalence’, . (Retrieved: August 26, 2013).
  • Xu, J. and H. Chen (2009) ‘Untangling Criminal Networks: A Case Study Intelligence and Security Informatics’, . (Retrieved: August 26, 2013).

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.doi-10_1515_irsr-2013-0021
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