Transitivity vs Preferential Attachment: Determining the Driving Force Behind the Evolution of Scientific Co-Authorship Networks
Transitivity vs Preferential Attachment: Determining the Driving Force Behind the Evolution of Scientific Co-Authorship Networks
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传递性与优先依恋：确定科学合作网络演变背后的驱动力
DOI：
10.1007/978-3-319-96661-8_28
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Hidetoshi Shimodaira
中科院分区：
文献类型：
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作者：
Masaaki Inoue;Thong Pham;Hidetoshi Shimodaira
我们提出了一种方法的非参数联合估计的优先连接和复杂网络中的传递性，相对于传统的方法，要么估计一个机制，在隔离或联合估计假设一些功能的形式。我们将我们的方法应用于复杂网络领域的学者，高能物理学的物理学家和《战略管理杂志》的作者之间的三个科学合著网络。非参数的方法揭示了复杂的趋势，优先连接和传递性，将无法在传统的参数方法。在所有的网络中，有一个共同的合作者与另一个科学家增加至少五倍的机会，一个将与该科学家合作。最后，通过量化每种机制的贡献，我们发现，虽然传递性在高能物理网络中主导了优先连接，但优先连接是其余两个网络演化的主要驱动力。
We propose a method for the non-parametric joint estimation of preferential attachment and transitivity in complex networks, as opposite to conventional methods that either estimate one mechanism in isolation or jointly estimate both assuming some functional forms. We apply our method to three scientific co-authorship networks between scholars in the complex network field, physicists in high-energy physics, and authors in the Strategic Management Journal. The non-parametric method revealed complex trends of preferential attachment and transitivity that would be unavailable under conventional parametric approaches. In all networks, having one common collaborator with another scientist increases at least five times the chance that one will collaborate with that scientist. Finally, by quantifying the contribution of each mechanism, we found that while transitivity dominates preferential attachment in the high-energy physics network, preferential attachment is the main driving force behind the evolutions of the remaining two networks.