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Mathematical Modeling in Social Network Analysis: Using TOPSIS to Find Node Influences in a Social Network

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Authors
Fox, William P.
Everton, Sean F.
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2013
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Abstract
In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, 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 measures 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 TOPSIS to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs 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 from Knoke and Wood. We discuss some basic sensitivity analysis can may be applied to the methods. We find the use of TOPSIS as a flexible method to weight the criterion based upon the decision makers’ inputs or the topology of the network.
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Journal of Mathematics and System Science 3:531-41
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Defense Analysis (DA)
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Fox, William P., and Sean F. Everton. 2013. "Mathematical Modeling in Social Network Analysis: Using TOPSIS to Find Node Influences in a Social Network." Journal of Mathematics and System Science 3:531-41. http://www.davidpublishing.com/show.html?14534
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This 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.
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