Research Of Spreading Dynamics On Complex Networks In Social Environment

Complex network is one of the most effective tool to study the evolution and dynamics of the vast majority of real systems,such as the disease spreading,information diffusion.The spreading dynamics on complex networks has been one of the most studied topics in the network science.It provides a strong theoretical support for predicting and controlling the real social system.It is affected by large numbers of social factors to predict and control the information and disease spreading.For example,the spreading size of rumor is determined by to what extent each individual would trust it;The investment of public resource and the support from families and friends can impact the recovery rate of infected individuals in the outbreak of epidemics,and then the infected size and epidemic threshold would be altered.The classical epidemic models are abstracted from real spreading processes,and ignore the influence of the real social factors.To study the impact of social factors on the the spreading dynamics,a thorough research in the following several aspects has been carried on:First of all,the impact of individual resources on the spreading dynamics has been studied.For this purpose,a coupled model of disease spreading and resource allocation was proposed.In this model,the recovery of the infected individuals in the contact network depends on the resources received from the healthy neighbors in social networks.First,this dissertation investigated how degree heterogeneity affects the spreading dynamics.Using theoretical analysis and simulations,it was found that degree heterogeneity promotes disease spreading.The phase transition of the infected density is hybrid.Namely,the infected density versus the transition rates for infection experiences continuous transition and discontinuous transition successively at the two thresholds.It was also found that hysteresis loop in the transition of the infected density appeared.Further,the question of how an overlap in the edges between two layers affects the spreading dynamics.It was found that with the increase of edge overlap between two layers,the infected density versus the transition rates for infection changes from hybrid transition to continuous transition.In addition,the edge overlap allows an epidemic outbreak when the transmission rate is below the first invasion threshold,but suppresses any explosive transition when the transmission rate is above the first invasion threshold.Secondly,the impact of allocation strategies of individual resource on the spreading dynamics of disease was studied.To find an effective resource allocation strategy,the infectiousness of each infected node has been taken into consideration.By studying the interplay between the resource allocation and epidemic spreading,it was found that the preferential resource allocation has so called “double-edged” sword effects on the disease spreading.Namely,when there is a small transmission rate,the infected density at the steady state decreases with the increment of degree of resource allocation preference.When there is a large transmission rate,the infected density increases with the increment of the degree of the preference,but the resource allocation is determined by the stage of epidemic spreading.Namely,in the early stage of the disease spreading,resources should be allocated preferentially to the high infectious nodes similar to the case of a small transmission rate.While after the early stage,resources should be allocated to the low infectious nodes.Usually,in the process of disease control,resources are either controlled globally by the government or allocated locally among individuals.Here,to explore systematically which of the two strategies is more efficient in suppressing the outbreaks of disease,a hybrid strategy is proposed,in which,a tunable parameter is introduced to tune the preference of global and local resource allocation.By studying the interplay between the resource allocation and disease spreading based on a generalized susceptible–infected–susceptible model,it was found that the global resource allocation has more advantages in controlling disease than local allocation.Besides,there is first order phase transition of the final infected fraction of nodes on homogeneous networks,however,the transition type changes from hybrid transitions to first order transition at a critical value of the tunable parameter on heterogeneous networks.At last,the interplay between the diffusion of individual resources and disease spreading was investigated.Resource diffusion is a ubiquitous phenomenon,but how it impacts epidemic spreading has received little study.To this end,a model that couples epidemic spreading and resource diffusion in multiplex networks was proposed.To quantify the degree of preferential diffusion,a bias parameter that controls the resource diffusion is proposed.Through extensive simulations,it was found that the preferential resource diffusion can change phase transition type of the fraction of infected nodes.When the degree of inter-layer correlation is below a critical value,increasing the bias parameter changes the phase transition from double continuous to single continuous.When the degree of inter-layer correlation is above a critical value,the phase transition changes from multiple continuous to first discontinuous and then to hybrid.It was also found that there is an optimal resource strategy at each fixed degree of inter-layer correlation under which the threshold reaches a maximum and the disease can be maximally suppressed.In addition,the optimal controlling parameter increases as the degree of inter-layer correlation increases.Moreover,there is a close interplay between the disease spreading on contact network and corresponding information propagation on communication network.Especially,it will be of much interest when there are certain overlaps between the topological edges of communication network and contact network.In this dissertation,the effect of inter-layer edge overlap on the asymmetrically interacting spreading dynamics of disease and information was studied,mainly including the final fraction of infected nodes and the epidemic threshold Though extensive simulations,we find that there is a so called “double-edged sword” effect on epidemic spreading and information propagation.Namely,when the disease spreads faster than information,a smaller amount of overlapping edges is able to effectively inhibit the epidemic spreading.On the contrary,when the information propagates more quickly than disease spreads,the more overlapping edges are,the better the epidemic spreading is suppressed.In further,it was shown that the epidemic threshold is improved when the overlapping edges increase.