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dc.contributor.advisorBorer, Douglas
dc.contributor.authorFernandes, Antione C.
dc.contributor.authorTaylor, Travis J.
dc.dateDec-15
dc.date.accessioned2016-02-17T18:38:52Z
dc.date.available2016-02-17T18:38:52Z
dc.date.issued2015-12
dc.identifier.urihttp://hdl.handle.net/10945/47943
dc.description.abstractAs the security landscape changes, the importance of strong and influential partnerships for security cooperation (SC) increases. The process of selecting the best possible partners should not be neglected; tools to accomplish this task may already exist. Recently, the use of social network analysis (SNA) has allowed the military to map dark networks of terrorist organizations and selectively target key elements. SNA data collection and analysis efforts remain focused on these terrorist networks, whereas friendly or light networks have been relatively neglected. This thesis highlights the importance of analyzing light networks for SC and introduces the concept of dim networks. These are networks that consist of friendly actors whose connections to external organizations may not be public. This thesis has potential to improve partner security force engagement selection through the use of SNA principles, methods, and software, yielding several dividends. First, it provides a commander with a detailed understanding of the foreign units involved in SC, which allows for development of a more focused engagement strategy. Second, it allows SC planners to invest time and resources on the partner security forces that most effectively advance the commander’s engagement priorities. Third, it reinforces the collection of network-related data on organizations the U.S. military cooperates with and the importance of analyzing that empirical data to improve SC.en_US
dc.description.urihttp://archive.org/details/dimnetworksutili1094547943
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleDim networks: the utility of social network analysis for illuminating partner security force networksen_US
dc.typeThesisen_US
dc.contributor.secondreaderRice, Ian
dc.contributor.departmentDefense Analysis (DA)
dc.subject.authorsocial network analysisen_US
dc.subject.authordark networksen_US
dc.subject.authorlight networksen_US
dc.subject.authordim networksen_US
dc.subject.authorsecurity cooperationen_US
dc.subject.authorSoutheast Asiaen_US
dc.subject.authornetworken_US
dc.subject.authorSpecial Operationsen_US
dc.subject.authorPhilippinesen_US
dc.description.serviceMajor, United States Armyen_US
etd.thesisdegree.nameMaster of Science in Defense Analysisen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineDefense Analysisen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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