复杂知识网络的结构特征对知识流动的影响

Effects of structural characteristics of complex knowledge network on knowledge flow

利用Jackson算法构建了知识网络的计算实验模型.该知识网络模型具备典型社会网络的五大特征.通过仿真试验探讨了单个虚拟的知识网络中具有不同属性的知识结点其知识水平演化的规律,两个具有不同知识水平的虚拟网络间建立知识合作联系的不同机制对落后网络和先进网络间知识扩散程度的不同影响,以及落后网络的网络密度和连接权重对网络间知识扩散程度的不同影响.

A computational model based on Jackson＇ s algorithm is proposed to form the knowledge networks, which possess five typical structural characteristics of complex social networks. Through simulation experiments, the knowledge evolution of different knowledge nodes with different characteristics is investigated. The fact is explored. How the diverse connecting mechanisms between networks A and B differentially influence the co-evolution of the knowledge levels of both networks. Moreover, the effects of the density and connecting weights of a less-developed network on knowledge flow between networks are analyzed.