New paper with Fragkiskos Papadopoulos explains overlap in multiplex networks by persistent links and network geometry, with applications to link prediction. See “Link persistence and conditional distances in multiplex networks” at https://arxiv.org/abs/1807.01190.
I have prepared a compact infographic about geometric correlations in multiplex networks and their applications/use cases:
I gave three talks at the NetSci 2018 conference in Paris this week. Here are the slides from my presentations:
I have been awarded the 3rd place at the NetSci Society Young Initiative for Best Talk Pitch for my video promoting our paper “Geometric correlations mitigate the extreme vulnerability of multiplex networks against targeted attacks” (Phys. Rev. Lett. 118, 218301). You can watch the video below, and I would be happy to see you at my talk in Paris on Wed 13.6. at 2:45pm in A2 (http://iuni.iu.edu/netsci2018/cam/#/event/2447).
My work with Dirk Helbing entitled “Topological enslavement in evolutionary games on correlated multiplex networks” has now been published in New Journal of Physics. You can read the paper at http://iopscience.iop.org/article/10.1088/1367-2630/aac155
Abstract: Governments and enterprises strongly rely on incentives to generate favorable outcomes from social and strategic interactions between individuals. The incentives are usually modeled by payoffs in evolutionary games, such as the prisoners dilemma or the harmony game, with imitation dynamics. Adjusting the incentives by changing the payoff parameters can favor cooperation, as found in the harmony game, over defection, which prevails in the prisoner’s dilemma. Here, we show that this is not always the case if individuals engage in strategic interactions in multiple domains. In particular, we investigate evolutionary games on multiplex networks where individuals obtain an aggregate payoff. We explicitly control the strength of degree correlations between nodes in the different layers of the multiplex. We find that if the multiplex is composed of many layers and degree correlations are strong, the topology of the system enslaves the dynamics and the final outcome, cooperation or defection, becomes independent of the payoff parameters. The fate of the system is then determined by the initial conditions.
My work with Dijana Tolić and Nino Antulov-Fantulin “Simulating SIR processes on networks using weighted shortest paths” has been published in Scientific Reports: https://www.nature.com/articles/s41598-018-24648-w.
Abstract: We present a framework to simulate SIR processes on networks using weighted shortest paths. Our framework maps the SIR dynamics to weights assigned to the edges of the network, which can be done for Markovian and non-Markovian processes alike. The weights represent the propagation time between the adjacent nodes for a particular realization. We simulate the dynamics by constructing an ensemble of such realizations, which can be done by using a Markov Chain Monte Carlo method or by direct sampling. The former provides a runtime advantage when realizations from all possible sources are computed as the weighted shortest paths can be re-calculated more efficiently. We apply our framework to three empirical networks and analyze the expected propagation time between all pairs of nodes. Furthermore, we have employed our framework to perform efficient source detection and to improve strategies for time-critical vaccination.
I am happy to announce that I will give a talk at the Controlling Complex Networks: When Control Theory Meets Network Science Satellite Symposium of NetSci2018 in the lovely city of Paris. The Symposium will take place June 11, 2018 (8:30am–6:05pm).
For more information, please visit https://scholar.harvard.edu/yyl/network-control-2018