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Dynamic Social Network Modeling and Analysis Workshop Summary and Papers (2003) / Chapter Skim
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Social Networks: Threat Networks and Threatened Networks
Pages 187-194

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
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From page 187...
... Our scientific goal is to uncover common principles governing the behavior of a range of social networks. Our practical goal is to use this understanding to den velop specific strategies to destroy threat networks and, in parallel, to develop specific strategies to defend threatened social networks against attack.
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From page 188...
... It is established that random immunization of a large fraction of the population fails to prevent epidemics of diseases that spread upon contact between infected individuals; for example, Malaria requires 99% of the population to be immunized in order to stop epidemic spreading [4,54. On the other hand, targeted immunization of the most-connected individuals requires global knowledge of the topology of the social network in question, rendering 99% immunization impractical.
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From page 189...
... The network is fully resilient to the random failure of sites and is extremely vulnerable to intentional attack. This analytical approach is being developed to study realistic social networks—e.g., where known correlations between individuals are included where the measured DYNAMIC SOCKS NETWO~MODEL~G kD TRYSTS 189
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From page 190...
... 4.4 Optimizing the Stability of Threatened Networks We are using the analytical approach we developed to calculate the percolation threshold for a given network t11,12] , in order to design topologies that improve the stability of scale-free networks under both random failures and intentional attacks.
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From page 191...
... These methods will also help to identity weaknesses and thereby protect threatened networks. 6 Discussion We are seeking to test whether concepts and methods of statistical physics such as scaling and percolation theory can be usefully applied to social networks, with special emphasis on social networks such as sexual networks and threatened networks.
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From page 192...
... We also were among the first to identify seal - free networks in certain social systems Id sexual networks [14-16] , and we developed an approach for classifying network topologies t173.
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From page 193...
... L Goldberger, Quantification of Scaling Exponents and Crossover Phenomena in Nonstationary Heartbeat Time Series" [P~oc.
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Key Terms

  • threatened networks
  • social network
  • sexual networks
  • dynamic social
  • percolation theory

  • infected individuals
  • analytical approach
  • statistical physics
  • random immunization
  • intentional attacks

  • data flow
  • topological structures
  • prevent epidemics
  • geographical distance
  • real networks

  • recent results
  • percolation approach
  • random failure
  • transport properties
  • trust networks

  • random failures
  • preliminary results
  • efficient immunization
  • connectivity distribution
  • topological properties

  • designing efficient
  • recent advances
  • threatened social
  • specific strategies
  • global knowledge


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