Research collaborations provide the foundation for scientific advances, but we have only recently begun to understand how they form and grow on a global scale. Here we analyze a model of the growth of research collaboration networks to explain the empirical observations that the number of collaborations scales superlinearly with institution size, though at different rates (heterogeneous densification), the number of institutions grows as a power of the number of researchers (Heaps' law) and institution sizes approximate Zipf's law. This model has three mechanisms: (i) researchers are preferentially hired by large institutions, (ii) new institutions trigger more potential institutions, and (iii) researchers collaborate with friends-of-friends. We show agreement between these assumptions and empirical data, through analysis of co-authorship networks spanning two centuries. We then develop a theoretical understanding of this model, which reveals emergent heterogeneous scaling such that the number of collaborations between institutions scale with an institution's size.
翻译:科研合作为科学进步提供了基础,但我们直到最近才开始理解它们是如何形成和在全球规模上成长的。 我们在这里分析研究协作网络增长的模型,以解释经验性观察,即合作数量与机构规模相比超线,尽管速度(异质密度)不同,机构数量随着研究人员人数(蜂窝法)和机构规模的增加而增长,这三种机制大致是齐普夫法律。这个模型有三个机制:(一) 研究人员优先受雇于大型机构,(二) 新的机构激发更多的潜在机构,以及(三) 研究人员与朋友合作。我们通过分析跨两个世纪的共同作者网络,显示了这些假设与经验数据之间的一致。然后,我们对这一模型形成了一种理论理解,它揭示出新出现的各种差异的尺度,即机构规模与机构规模之间的协作数量。