A paper on "Evolution of the Global Risk Network Mean-Field Stability Point," by X. Niu, A. Mousawi, N. Derzsy, X. Lin, G. Korniss and B.K. Szymanski has been published in Proc. 6th Int. Conf. Complex Networks Lyon, France Nov 29-Dec 1, 2017.

A paper titled "Evolution of the Global Risk Network Mean-Field Stability Point," by Xiang Niu, Alaa Mousawi, Noemi Derzsy, Xin Lin, Gyorgy Korniss and Boleslaw K. Szymanski has been presented at the conference and published in Proc. 6th International Conference on Complex Networks and Their Applications, Complex Networks, Lyon, France Nov 29-Dec 1, 2017, Studies in Artificial Intelligence, vol. 689, Springer, Zurich, Switzerland, pp. 1124-1134. With a steadily growing human population and rapid advancements in technology, the global human network is increasing in size and connection density. This growth exacerbates networked global threats and can lead to unexpected consequences such as global epidemics mediated by air travel, threats in cyberspace, global governance, etc. A quantitative understanding of the mechanisms guiding this global network is necessary for proper operation and maintenance of the global infrastructure. Each year the World Economic Forum publishes an authoritative report on global risks, and applying this data to a CARP model, we answer critical questions such as how the network evolves over time. In the evolution, we compare not the current states of the global risk network at different time points, but its steady state at those points, which would be reached if the risk were left unabated. Looking at the steady states show more drastically the differences in the challenges to the global economy and stability the world community had faced at each point of the time. Finally, we investigate the influence between risks in the global network, using a method successful in distinguishing between correlation and causation. All results presented in the paper were obtained using detailed mathematical analysis with simulations to support our findings.