Mining for geographically disperse communities in social networks by leveraging distance modularity

@article{Shakarian2013MiningFG,
  title={Mining for geographically disperse communities in social networks by leveraging distance modularity},
  author={P. Shakarian and P. Roos and Devon Callahan and C. Kirk},
  journal={Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining},
  year={2013}
}
  • P. Shakarian, P. Roos, +1 author C. Kirk
  • Published 2013
  • Computer Science, Physics
  • Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
  • Social networks where the actors occupy geospatial locations are prevalent in military, intelligence, and policing operations such as counter-terrorism, counter-insurgency, and combating organized crime. These networks are often derived from a variety of intelligence sources. The discovery of communities that are geographically disperse stems from the requirement to identify higher-level organizational structures, such as a logistics group that provides support to various geographically… CONTINUE READING
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