Social media have dramatically changed the mode of information dissemination.Various models and algorithms have been developed to model information diffusion and address the influence maximization problem in complex s...Social media have dramatically changed the mode of information dissemination.Various models and algorithms have been developed to model information diffusion and address the influence maximization problem in complex social networks.However,it appears difficult for state-of-the-art models to interpret complex and reversible real interactive networks.In this paper,we propose a novel influence diffusion model,i.e.,the Operator-Based Model(OBM),by leveraging the advantages offered from the heat diffusion based model and the agent-based model.The OBM improves the performance of simulated dissemination by considering the complex user context in the operator of the heat diffusion based model.The experiment obtains a high similarity of the OBM simulated trend to the real-world diffusion process by use of the dynamic time warping method.Furthermore,a novel influence maximization algorithm,i.e.,the Global Topical Support Greedy algorithm(GTS-Greedy algorithm),is proposed corresponding to the OBM.The experimental results demonstrate its promising performance by comparing it against other classic algorithms.展开更多
In this paper, we introduce an asymmetric payoff distribution mechanism into the evolutionary prisoner＇s dilemma game （PDG） on Newman Watts social networks, and study its effects on the evolution of cooperation. Th...In this paper, we introduce an asymmetric payoff distribution mechanism into the evolutionary prisoner＇s dilemma game （PDG） on Newman Watts social networks, and study its effects on the evolution of cooperation. The asymmetric payoff distribution mechanism can be adjusted by the parameter α： if α〉 0, the rich will exploit the poor to get richer; if α 〈 0, the rich are forced to offer part of their income to the poor. Numerical results show that the cooperator frequency monotonously increases with c~ and is remarkably promoted when c~ 〉 0. The effects of updating order and self-interaction are also investigated. The co-action of random updating and self-interaction can induce the highest cooperation level. Moreover, we employ the Gini coefficient to investigate the effect of asymmetric payoff distribution on the the system＇s wealth distribution. This work may be helpful for understanding cooperative behaviour and wealth inequality in society.展开更多
Different approaches have been established for applications of social and complex networks involving biological systems, passing through collaborative systems in knowledge networks and organizational systems. In this ...Different approaches have been established for applications of social and complex networks involving biological systems, passing through collaborative systems in knowledge networks and organizational systems. In this latter application, we highlight the studies focused on the diffusion of information and knowledge in networks. However, most of the time, the propagation of information in these networks and the resulting process of creation and diffusion of knowledge, have been studied from static perspectives. Additionally, the very concept of diffusion inevitably implies the inclusion of the temporal dimension, due to that it is an essentially dynamic process. Although static analysis provides an important perspective in structural terms, the behavioral view that reflects the evolution of the relationships of the members of these networks over time is best described by temporal networks. Thus, it is possible to analyze both the information flow and the structural changes that occur over time, which influences the dynamics of the creation and diffusion of knowledge. This article describes the computational modeling used to elucidate the creation and diffusion of knowledge in temporal networks formed to execute software maintenance and construction projects, for the period between 2007 and 2013, in the SERVIÇO FEDERAL DE PROCESSAMENTO DE DADOS (FEDERAL DATA PROCESSING SERVICE-SERPRO)—a public organization that provides information and communication technology services. The methodological approach adopted for the study was based on techniques for analyzing social and complex networks and on the complementary extensions that address temporal modeling of these networks. We present an exploratory longitudinal study that enabled a dynamic and structural analysis of the knowledge networks formed by members of software maintenance and development project teams between 2007 and 2013. The study enabled identification of knowledge categories throughout this period, in addition to the determination that the networks have a structure with small-world and scale-free models. Finally, we concluded that, in general, the topologies of the networks studies had characteristics for facilitating the flow of knowledge within the organization.展开更多
We investigate the navigation process on a variant of the Watts-Strogatz small-world network model with local information. In the network construction, each vertex of an N x N square lattice sends out a long-range lin...We investigate the navigation process on a variant of the Watts-Strogatz small-world network model with local information. In the network construction, each vertex of an N x N square lattice sends out a long-range link with probability p. The other end of the link falls on a randomly chosen vertex with probability proportional to r^-α, where r is the lattice distance between the two vertices, and α ≥ 0. The average actual path length, i.e. the expected number of steps for passing messages between randomly chosen vertex pairs, is found to scale as a power-law function of the network size N^β, except when α is close to a specific value value, which gives the highest efficiency of message navigation. For a finite network, the exponent β depends on both α and p, and p αmin drops to zero at a critical value of p which depends on N. When the network size goes to infinity,β depends only only on α, and αmin is equal to the network dimensionality.展开更多
Based on previous works, we give further investigations on the Prisoners＇ Dilemma Game （PDG） on two different types of homogeneous networks, i.e. the homogeneous small-world network （HSWN） and the regular ring gr...Based on previous works, we give further investigations on the Prisoners＇ Dilemma Game （PDG） on two different types of homogeneous networks, i.e. the homogeneous small-world network （HSWN） and the regular ring graph. We find that the so-called resonance-like character can occur on both the networks. Different from the viewpoint in previous publications, we think the small-world effect may be unnecessary to produce this character. Therefore, over these two types of networks, we suggest a common understanding in the viewpoint of clustering coefficient. Detailed simulation results can sustain our viewpoint quite well. Furthermore, we investigate the Snowdrift Game （SG） on the same networks. The difference between the outputs of the PDG and the SG can also sustain our viewpoint.展开更多
In social networks, opinions diffusion often leads to relationships evolution. Then changes of relationships result in the change of balance degree of social system. We simulate the opinion diffusion on Barabasi &...In social networks, opinions diffusion often leads to relationships evolution. Then changes of relationships result in the change of balance degree of social system. We simulate the opinion diffusion on Barabasi & Albert (BA) network and Watts & Strogatz (WS) network to study the effects of the two types of networks, dynamical parameters and structural parameters on the balance degree of system. We employ the spectral analysis to quantify the balance degree of system before and after opinion propagation. The result reveals that it is very similar effect of BA networks and WS networks on it. However, it is opposite effects between dynamical parameters and structural parameters. The balance degree of system is proportional to the two dynamical factors (P,Q) at initial state and always inversely proportional to the two structural factors (,Pne) at initial and convergence state.展开更多
针对经典网络社区划分方法存在的划分结果难以理解的问题,基于源自物理学中核子场的拓扑势理论,提出针对具有聚类效应的社会网络和复杂网络的社区结点重要度排序算法.在算法中,首先利用NSP方法(network soft partitionbased on topologi...针对经典网络社区划分方法存在的划分结果难以理解的问题,基于源自物理学中核子场的拓扑势理论,提出针对具有聚类效应的社会网络和复杂网络的社区结点重要度排序算法.在算法中,首先利用NSP方法(network soft partitionbased on topological potential)依据结点在社区中所起的作用将其分为内部结点和边界结点,其次分别对内部结点和边界结点的重要性进行量化并排序,最后将2个排序结果进行拼接以构成最终的排序结果.实验表明,文中算法不但可以解决前述问题,而且具有和快速排序算法同样的时间复杂度.展开更多
文摘Social media have dramatically changed the mode of information dissemination.Various models and algorithms have been developed to model information diffusion and address the influence maximization problem in complex social networks.However,it appears difficult for state-of-the-art models to interpret complex and reversible real interactive networks.In this paper,we propose a novel influence diffusion model,i.e.,the Operator-Based Model(OBM),by leveraging the advantages offered from the heat diffusion based model and the agent-based model.The OBM improves the performance of simulated dissemination by considering the complex user context in the operator of the heat diffusion based model.The experiment obtains a high similarity of the OBM simulated trend to the real-world diffusion process by use of the dynamic time warping method.Furthermore,a novel influence maximization algorithm,i.e.,the Global Topical Support Greedy algorithm(GTS-Greedy algorithm),is proposed corresponding to the OBM.The experimental results demonstrate its promising performance by comparing it against other classic algorithms.
基金Project supported by the Major State Basic Research Development Program of China (Grant No. 2004CB318109)Program for New Century Excellent Talents in University of China (Grant No. NCET-07-0787)the National Natural Science Foundation of China (Grant No. 70601026)
文摘In this paper, we introduce an asymmetric payoff distribution mechanism into the evolutionary prisoner＇s dilemma game （PDG） on Newman Watts social networks, and study its effects on the evolution of cooperation. The asymmetric payoff distribution mechanism can be adjusted by the parameter α： if α〉 0, the rich will exploit the poor to get richer; if α 〈 0, the rich are forced to offer part of their income to the poor. Numerical results show that the cooperator frequency monotonously increases with c~ and is remarkably promoted when c~ 〉 0. The effects of updating order and self-interaction are also investigated. The co-action of random updating and self-interaction can induce the highest cooperation level. Moreover, we employ the Gini coefficient to investigate the effect of asymmetric payoff distribution on the the system＇s wealth distribution. This work may be helpful for understanding cooperative behaviour and wealth inequality in society.
文摘Different approaches have been established for applications of social and complex networks involving biological systems, passing through collaborative systems in knowledge networks and organizational systems. In this latter application, we highlight the studies focused on the diffusion of information and knowledge in networks. However, most of the time, the propagation of information in these networks and the resulting process of creation and diffusion of knowledge, have been studied from static perspectives. Additionally, the very concept of diffusion inevitably implies the inclusion of the temporal dimension, due to that it is an essentially dynamic process. Although static analysis provides an important perspective in structural terms, the behavioral view that reflects the evolution of the relationships of the members of these networks over time is best described by temporal networks. Thus, it is possible to analyze both the information flow and the structural changes that occur over time, which influences the dynamics of the creation and diffusion of knowledge. This article describes the computational modeling used to elucidate the creation and diffusion of knowledge in temporal networks formed to execute software maintenance and construction projects, for the period between 2007 and 2013, in the SERVIÇO FEDERAL DE PROCESSAMENTO DE DADOS (FEDERAL DATA PROCESSING SERVICE-SERPRO)—a public organization that provides information and communication technology services. The methodological approach adopted for the study was based on techniques for analyzing social and complex networks and on the complementary extensions that address temporal modeling of these networks. We present an exploratory longitudinal study that enabled a dynamic and structural analysis of the knowledge networks formed by members of software maintenance and development project teams between 2007 and 2013. The study enabled identification of knowledge categories throughout this period, in addition to the determination that the networks have a structure with small-world and scale-free models. Finally, we concluded that, in general, the topologies of the networks studies had characteristics for facilitating the flow of knowledge within the organization.
基金Supported by the National Natural Science Foundation of China under Grant No 10375008, and the National Basic Research Programme of China under Grant No 2003CB716302
文摘We investigate the navigation process on a variant of the Watts-Strogatz small-world network model with local information. In the network construction, each vertex of an N x N square lattice sends out a long-range link with probability p. The other end of the link falls on a randomly chosen vertex with probability proportional to r^-α, where r is the lattice distance between the two vertices, and α ≥ 0. The average actual path length, i.e. the expected number of steps for passing messages between randomly chosen vertex pairs, is found to scale as a power-law function of the network size N^β, except when α is close to a specific value value, which gives the highest efficiency of message navigation. For a finite network, the exponent β depends on both α and p, and p αmin drops to zero at a critical value of p which depends on N. When the network size goes to infinity,β depends only only on α, and αmin is equal to the network dimensionality.
基金Supported by the National Basic Research Programme of China under Grant No 2006CB705500, the National Natural Science Foundation of China under Grant Nos 60744003, 10635040, 10532060, 10472116 and 10404025, and the Specialized Research Fund for the Doctoral Programme of Higher Education of China.
文摘Based on previous works, we give further investigations on the Prisoners＇ Dilemma Game （PDG） on two different types of homogeneous networks, i.e. the homogeneous small-world network （HSWN） and the regular ring graph. We find that the so-called resonance-like character can occur on both the networks. Different from the viewpoint in previous publications, we think the small-world effect may be unnecessary to produce this character. Therefore, over these two types of networks, we suggest a common understanding in the viewpoint of clustering coefficient. Detailed simulation results can sustain our viewpoint quite well. Furthermore, we investigate the Snowdrift Game （SG） on the same networks. The difference between the outputs of the PDG and the SG can also sustain our viewpoint.
文摘In social networks, opinions diffusion often leads to relationships evolution. Then changes of relationships result in the change of balance degree of social system. We simulate the opinion diffusion on Barabasi & Albert (BA) network and Watts & Strogatz (WS) network to study the effects of the two types of networks, dynamical parameters and structural parameters on the balance degree of system. We employ the spectral analysis to quantify the balance degree of system before and after opinion propagation. The result reveals that it is very similar effect of BA networks and WS networks on it. However, it is opposite effects between dynamical parameters and structural parameters. The balance degree of system is proportional to the two dynamical factors (P,Q) at initial state and always inversely proportional to the two structural factors (,Pne) at initial and convergence state.
