title: Failure dynamics of the global risk network.
abstract: Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of likelihoods and influence of risks underlie a quantitative model of the global risk network dynamics. The modeled risks range from environmental to economic and technological, and include difficult to quantify risks, such as geo-political and social. Using the maximum likelihood estimation, we find the optimal model parameters and demonstrate that the model including network effects significantly outperforms the others, uncovering full value of the expert collected data. We analyze the model dynamics and study its resilience and stability. Our findings include such risk properties as contagion potential, persistence, roles in cascades of failures and the identity of risks most detrimental to system stability. The model provides quantitative means for measuring the adverse effects of risk interdependencies and the materialization of risks in the network.
authors.affiliation: 1] Social and Cognitive Networks Academic Research Center, Rensselaer Polytechnic Institute, Troy NY 12180 [2] Dept. of Computer Science, RPI, 110 8th Street, Troy, NY 12180 [3] Dept. of Computer Science &Management, Wroclaw University of Technology, 50-370 Wroclaw, Poland.
authors.forename: Boleslaw K
authors.initials: BK
authors.lastname: Szymanski
authors.affiliation: 1] Social and Cognitive Networks Academic Research Center, Rensselaer Polytechnic Institute, Troy NY 12180 [2] Dept. of Computer Science, RPI, 110 8th Street, Troy, NY 12180.
authors.forename: Xin
authors.initials: X
authors.lastname: Lin
authors.affiliation: 1] Social and Cognitive Networks Academic Research Center, Rensselaer Polytechnic Institute, Troy NY 12180 [2] Dept. of Computer Science, RPI, 110 8th Street, Troy, NY 12180 [3] Dept. of Physics, Applied Physics and Astronomy, RPI, 110 8th Street, Troy, NY 12180.
authors.forename: Andrea
authors.initials: A
authors.lastname: Asztalos
authors.affiliation: 1] Social and Cognitive Networks Academic Research Center, Rensselaer Polytechnic Institute, Troy NY 12180 [2] Dept. of Computer Science, RPI, 110 8th Street, Troy, NY 12180 [3] Dept. of Physics, Applied Physics and Astronomy, RPI, 110 8th Street, Troy, NY 12180.
authors.forename: Sameet
authors.initials: S
authors.lastname: Sreenivasan
mesh_terms: D008962:Models, Theoretical; D012306:Risk