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Michael Gabbay

Senior Principal Physicist

Email

mgabbay@apl.uw.edu

Phone

206-616-8528

Biosketch

Dr. Gabbay's current research involves the development of mathematical models and computational simulations of network dynamics, focusing on social and political systems. He has also conducted research in the areas of nonequilibrium pattern formation, coupled oscillator dynamics, sensor development, and data analysis algorithms. His work has appeared in physics, engineering, biology, and political science publications. Dr. Gabbay received a B.A. in physics from Cornell University and a Ph.D. in physics from the University of Chicago with a specialization in nonlinear dynamics.

Education

B.A. Physics, Cornell University, 1985

M.S. Physics, University of Chicago, 1987

Ph.D. Physics, University of Chicago, 1997

Publications

2000-present and while at APL-UW

Fratricide in rebel movements: A network analysis of Syrian militant infighting

Gade, E.K., M.M. Hafez, and M. Gabbay, "Fratricide in rebel movements: A network analysis of Syrian militant infighting," J. Peace Res., 56, 321-335, doi:10.1177/0022343318806940, 2019.

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1 May 2019

Violent conflict among rebels is a common feature of civil wars and insurgencies. Yet, not all rebel groups are equally prone to such infighting. While previous research has focused on the systemic causes of violent conflict within rebel movements, this article explores the factors that affect the risk of conflict between pairs of rebel groups. We generate hypotheses concerning how differences in power, ideology, and state sponsors between rebel groups impact their propensity to clash and test them using data from the Syrian civil war. The data, drawn from hundreds of infighting claims made by rebel groups on social media, are used to construct a network of conflictual ties among 30 rebel groups. The relationship between the observed network structure and the independent variables is evaluated using network analysis metrics and methods including assortativity, community structure, simulation, and latent space modeling. We find strong evidence that ideologically distant groups have a higher propensity for infighting than ideologically proximate ones. We also find support for power asymmetry, meaning that pairs of groups of disparate size are at greater risk of infighting than pairs of equal strength. No support was found for the proposition that sharing state sponsors mitigates rebels’ propensity for infighting. Our results provide an important corrective to prevailing theory, which discounts the role of ideology in militant factional dynamics within fragmented conflicts.

Opinion network modeling and experiment

Gabbay, M., "Opinion network modeling and experiment," Proc., 5th International Conference on Applications in Nonlinear Dynamics, Maui, Hawaii, 5-9 August, 2018 . V. In, P. Longhini and A. Palacios, eds., 174-185 (Springer, Cham, 2019).

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17 Apr 2019

We present a model describing the temporal evolution of opinions due to interactions among a network of individuals. This Accept-Shift-Constrict (ASC) model is formulated in terms of coupled nonlinear differential equations for opinions and uncertainties. The ASC model dynamics allows for the emergence and persistence of majority positions so that the mean opinion can shift even for a symmetric network. The model also formulates a distinction between opinion and rhetoric in accordance with a recently proposed theory of the group polarization effect. This enables the modeling of discussion-induced shifts toward the extreme without the typical modeling assumption of greater resistance to persuasion among extremists. An experiment is described in which triads engaged in online discussion. Simulations show that the ASC model is in qualitative and quantitative agreement with the experimental data.

Integrating computational modeling and experiments: Toward a more unified theory of social influence

Gabbay, M., "Integrating computational modeling and experiments: Toward a more unified theory of social influence," in Social-Behavioral Modeling for Complex Systems, P.K. Davis, A. O'Mahony, and J. Pfautz, eds., 279-310 (John Wiley & Sons, 2019).

1 Apr 2019

More Publications

Acoustics Air-Sea Interaction & Remote Sensing Center for Environmental & Information Systems Center for Industrial & Medical Ultrasound Electronic & Photonic Systems Ocean Engineering Ocean Physics Polar Science Center
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