Applying Flow Algorithms to Deconstruct Social Networks

dc.contributor.advisorClark, Terryen_US
dc.contributor.authorWagner, Sophie J.F.en_US
dc.contributor.cuauthorWagner, Sophie J.F.en_US
dc.date.accessioned2015-05-22T14:16:11Z
dc.date.available2015-06-01T08:40:08Z
dc.date.issued2014-05-14
dc.degree.committeeWierman, Marken_US
dc.degree.committeeMartin, Jamesen_US
dc.degree.disciplineInternational Relations (graduate program)en_US
dc.degree.grantorGraduate Schoolen_US
dc.degree.levelMA (Master of Arts)en_US
dc.degree.nameM.A. in International Relationsen_US
dc.description.abstractDeconstructing social networks is a matter of particular importance when considering terror or criminal networks. Apart from discussions of general strategies, identifying which nodes or edges should be removed from a network to pull it apart fastest is a subject on which little research has been done. This thesis proposes a method to deconstruct networks based on network flow algorithms that can identify edges which bottleneck a network. The models test the efficiency of this method against two standard strategies across several ideal network types.en_US
dc.description.noteProQuest Traditional Publishing Optionen_US
dc.embargo.terms2015-06-01
dc.identifier.urihttp://hdl.handle.net/10504/68812
dc.language.isoen_USen_US
dc.publisherCreighton Universityen_US
dc.publisher.locationOmaha, Nebraskaen_US
dc.rightsCopyright is retained by the Author. A non-exclusive distribution right is granted to Creighton University and to ProQuest following the publishing model selected above.en_US
dc.rights.holderSophie J.F. Wagneren_US
dc.titleApplying Flow Algorithms to Deconstruct Social Networksen_US
dc.typeThesis
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