2013 MiningforGeographicallyDisperse

• (Shakarian et al., 2013) ⇒ Paulo Shakarian, Patrick Roos, Devon Callahan, and Cory Kirk. (2013). “Mining for Geographically Disperse Communities in Social Networks by Leveraging Distance Modularity.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2488194

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222013%22+Mining+for+Geographically+Disperse+Communities+in+Social+Networks+by+Leveraging+Distance+Modularity
• http://dl.acm.org/citation.cfm?id=2487575.2488194&preflayout=flat#citedby

Quotes

Author Keywords

• Complex networks; geospatial reasoning; sociology

Abstract

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 disperse terrorist cells. We apply a variant of Newman-Girvan modularity to this problem known as distance modularity. To address the problem of finding geographically disperse communities, we modify the well-known Louvain algorithm to find partitions of networks that provide near-optimal solutions to this quantity. We apply this algorithm to numerous samples from two real-world social networks and a terrorism network data set whose nodes have associated geospatial locations. Our experiments show this to be an effective approach and highlight various practical considerations when applying the algorithm to distance modularity maximization. Several military, intelligence, and law-enforcement organizations are working with us to further test and field software for this emerging application.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 MiningforGeographicallyDisperse	Paulo Shakarian Patrick Roos Devon Callahan Cory Kirk			Mining for Geographically Disperse Communities in Social Networks by Leveraging Distance Modularity				10.1145/2487575.2488194		2013