研究科学知识演化的动力及规律是探究科学知识创造及发展过程的关键.基于复杂网络的方法建立了科学知识的演化模型,揭示了知识演化的马太效应中潜隐的时间因素的作用,时间效应一定程度上平抑了度择优所导致的马太效应的负面影响.模型通过引入度择优和时间优先连接以反映了科学知识的继承与更新过程,其中度择优机制保证对经典科学理论的继承,时间优先机制促使对新近知识的吸收.数理分析与模拟结果表明度择优所体现的马太效应的作用是全局性的,时间效应所体现的后发优势的影响则是局部的.%Research on the evolution and dynamics is the key point to explore the processes of the creation and development of scientific knowledge. By using the method of complex networks, we constructed a evolving model which revealed the effect of the time factor on the evolution of knowledge and the relationship between it and Matthew Effect, and discovered that the time effect decreases the adverseness of Matthew Effect. The model introduced both degree and time preferential attachments to describe the accepting and updating processes of scientific knowledge. The degree preferential attachment ensures the acceptance of classic theory, and the time preferential attachment encourages the absorption of recent knowledge. Simulation results showed that the effect of preferential attachment, which produced Matthew Effect, is overarching; and the effect of time attachment is partial.
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