科研合作超网络下的知识扩散演化模型研究

发布时间：2018-03-14 05:15

本文选题：科研合作　切入点：超网络　出处：《情报学报》2017年03期 　论文类型：期刊论文

【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—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。
[Abstract]:In order to explore the evolution law and dynamic mechanism of knowledge diffusion in scientific research cooperation network, This paper introduces the theory of complex network and hypergraph to construct an evolutionary model of knowledge diffusion based on scientific research cooperation supernetwork. By reproducing the real network organization knowledge transmission behavior, the different network structure characteristics in scientific research cooperative network are revealed. Node preference selection, knowledge growth and aging, and the dynamic relationship between knowledge diffusion path and knowledge diffusion process. Considering different individuals' knowledge self-growth and knowledge absorption ability, the network average knowledge level and knowledge diffusion rate are adopted. The simulation results show that the scale-free scientific research cooperative network can improve the average knowledge level and the knowledge diffusion rate to the maximum extent. The preference choice of node knowledge stock can promote the effective diffusion of knowledge more than the preferred connection of node degree, and the effect is not significant. The degradation of distributed nodes greatly reduces the average knowledge level and the rate of knowledge diffusion. The influence of the knowledge growth of new node and the degradation of old node on the knowledge level of the whole network can be balanced at some time, and the individual realizes the growth of self-knowledge-genetic inheritance and sudden variation. On the basis of scale-free network diffusion model, it also produces different oscillatory effects on knowledge diffusion. It is of great significance to the structure of scientific research and the cooperation and communication between scientific research workers and the improvement of their performance.
【作者单位】：武汉大学信息资源研究中心;
【基金】：国家自然科学基金“科研团队动态演化规律研究”(71273196)
【分类号】：G353.1;O157.5

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