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dc.contributor.authorFox, William P.
dc.contributor.authorEverton, Sean F.
dc.date2015
dc.date.accessioned2017-05-12T17:25:01Z
dc.date.available2017-05-12T17:25:01Z
dc.identifier.citationFox, William P., and Sean F. Everton. 2015. "Using Data Envelopment Analysis and Analytical Hierarchy Process to Find Node Influences in a Social Network." Journal of Defense Modeling and Simulation 12(2):157-65. http://dms.sagepub.com/content/early/2014/01/07/1548512913518273en_us
dc.identifier.urihttp://hdl.handle.net/10945/53060
dc.descriptionJournal of Defense Modeling and Simulation 12(2):157-65en_US
dc.description.abstractIn a social network analysis the output provided includes many measures and metrics. For each of these measures and metrics, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the mea- sures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes? Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply two procedures to analyze these outputs to find the most influential nodes as a function of the decision mak- ers’ inputs. We use data envelopment analysis as a method to optimize efficiency of the nodes over all criteria and use the analytical hierarchy process (AHP) as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature: the kite network and the information flow network. We discuss some basic sensitivity analysis that can be applied to the methods. We find the AHP method as the most flexible method to weight the criterion based upon the decision makers’ inputs or the topology of the network.en_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.titleUsing Data Envelopment Analysis and Analytical Hierarchy Process to Find Node Influences in a Social Networken_US
dc.typeArticleen_US
dc.contributor.departmentDefense Analysis (DA)en_US


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