Emergence of scaling in complex substitutive systems
Emergence of scaling in complex substitutive systems
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DOI：
10.1038/s41562-019-0638-y
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发表时间：
2019-08-01
影响因子：
29.9
通讯作者：
Wang, Dashun
中科院分区：
文献类型：
--
作者：
Jin, Ching;Song, Chaoming;Wang, Dashun
扩散过程是人类互动的核心。当前建模框架的一个常见预测是，最初的传播动力遵循指数增长。在这里，我们发现，从移动手机到汽车，从智能手机应用程序到科学领域，早期的增长模式遵循非整数指数的幂定律。我们通过分析追踪360万名更换不同手机的人的独特数据，检验了特定于替代动态的机制可能发挥作用的假设。我们揭示了三种控制替代的通用成分，使我们能够开发一个最小替代模型，该模型不仅解释了幂定律增长，而且将个别成分的不同增长轨迹压缩到一条曲线中。这些结果提供了对不同领域出现的幂定律早期增长模式的机械论理解，并表明替代动态受到强健的自组织原则的支配，这些原则超出了单个系统的特殊性。
Diffusion processes are central to human interactions. One common prediction of the current modelling frameworks is that initial spreading dynamics follow exponential growth. Here we find that, for subjects ranging from mobile handsets to automobiles and from smartphone apps to scientific fields, early growth patterns follow a power law with non-integer exponents. We test the hypothesis that mechanisms specific to substitution dynamics may play a role, by analysing unique data tracing 3.6 million individuals substituting different mobile handsets. We uncover three generic ingredients governing substitutions, allowing us to develop a minimal substitution model, which not only explains the power-law growth, but also collapses diverse growth trajectories of individual constituents into a single curve. These results offer a mechanistic understanding of power-law early growth patterns emerging from various domains and demonstrate that substitution dynamics are governed by robust self-organizing principles that go beyond the particulars of individual systems.