中文摘要：

为探究科研合作网络中知识扩散的演化规律和动力机制，引入复杂网络和超图数学理论构建一种基于科研合作超网络的知识扩散演化模型。通过再现真实的网络组织知识传播行为，揭示科研合作网络中不同网络结构特征、结点偏好性选择、知识增长老化以及知识扩散途径与知识传播扩散过程的动态关系。考虑不同个体知识自我增长以及知识吸收能力，采用网络平均知识水平、知识扩散速率、知识均衡程度作为衡量知识扩散效果的评价指标。仿真结果表明：具有无标度特征的科研合作网络能最大限度地提高网络平均知识水平和知识扩散速率；结点知识存量偏好性选择比结点度择优连接更能促进知识的有效扩散，其影响效果差异并不显著；集散结点的退化，极大降低网络的平均知识水平和知识扩散速率，新结点的知识增长与老结点的退化对整个网络知识水平的影响在某时刻能达到均衡；个体实现自我知识的增长一遗传继承和突发变异，在无标度网络扩散模型的基础上同样对知识扩散产生不同的震荡作用。研究影响知识扩散的要素以及要素的作用机理，对科研结构和科研工作者之间的合作交流和绩效的提高具有重要意义。

英文摘要：

In order to explore evolution regularity and dynamic mechanism of knowledge diffusion in scientific coop- eration network, this paper proposes a knowledge diffusion evolution model based on collaboration hypernetwork by introducing complex network and hyper-graph. Combined with knowledge dissemination behavior in real-world net- works organization, the article inspects the relation between knowledge diffusion and different structural characteris- tics, nodes preferential attachment, knowledge growth and deterioration, and knowledge diffusion paths, meanwhile, considering the differences of self-knowledge growth and knowledge absorption capacity which is correlated with the knowledge stock of receivers, the knowledge spillover effects and the correlation intensity of both, the average knowledge level, the knowledge diffusion rate, the knowledge balance degree and knowledge transient increment are elected to measure the growth and diffusion of knowledge and the adequacy of knowledge diffusion. The results show that the scale-free network has a most fast knowledge diffusion rate and highest average knowledge level; the knowledge stock preferential attachment mechanisms could bring more contributions to promote the effective diffu- sion of knowledge than the hyperdegree preferential attachment, there are no significant differences of promotional impact, though. Deterioration of hubs greatly reduces the average knowledge level and diffusion rate of entire net- work and achieves a balanced effect at certain point with the knowledge growth of new nodes. Individual knowledge self-growth approaches--genetic inheritance and abrupt variation exert different shocks to knowledge diffusion on the basis of the scale-flee network diffusion model. Though analyzing the infiuence factors and functional mechanism for knowledge diffusion, it has important significance on cooperation exchange and performance improvement for researchers.