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Dr Michael Gabbay

This chapter describes a quantitative methodology for the analysis and modelling of leadership networks which leverages research in complex systems, mainly nonlinear dynamical systems theory and network science. A prototype software package, PORTEND, is introduced implementing the methodology and using data from expert analysts to assess policy and factional outcomes with respect to the internal dynamics of a system of political actors. The methodology includes structural analysis methods, such as algorithms for analysing issue positions and community structure, and a simulation of nonlinear social influence dynamics. PORTEND’s capabilities are illustrated for an application to Iran involving fifteen leadership elites and seven issues. The factional structure of the Iranian leadership group is analysed first based on their issue positions, then with respect to the network of inter-actor influence relationships, and finally by a synthesis of the issue and network data. An application of the nonlinear social influence simulation to the nuclear issue is presented and its implications are discussed with respect to Iranian decision-making concerning the 2013_2015 nuclear negotiations.