TITLE:
Using Mathematical Models in Decision Making Methodologies to Find Key Nodes in the Noordin Dark Network
AUTHORS:
William P. Fox, Sean F. Everton
KEYWORDS:
Social Network Analysis, Multi-Attribute Decision Making, Analytical Hierarchy Process (AHP), Decision Criterion, Weighted Criterion, TOPSIS, Node Influence, Sensitivity Analysis, Average Weighted Ranks
JOURNAL NAME:
American Journal of Operations Research,
Vol.4 No.4,
July
25,
2014
ABSTRACT: A Dark Network is a network that cannot be accessed through tradition
means. Once uncovered, to any degree, dark network analysis can be accomplished
using the SNA software. The output of SNA software includes many measures and
metrics. For each of these measures and metric, the output in ORA additionally
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 best
methods to disrupt or deceive a given dark network. In the Noordin Dark network,
different nodes were identified as key nodes based upon the metric used. Our
goal in this paper is to use methodologies to identify the key players or nodes
in a Dark Network in a similar manner as we previously proposed in social
networks. We apply two multi-attribute decision making methods, a hybrid AHP
& TOPSIS and an average weighted ranks scheme, to analyze these outputs to
find the most influential nodes as a function of the decision makers’ inputs.
We compare these methods by illustration using the Noordin Dark Network with
seventy-nine nodes. We discuss sensitivity analysis that is applied to the
criteria weights in order to measure the change in the ranking of the nodes.