Vermont Complex Systems Center, Computational Story Lab, Vermont Advanced Computing Core, Department of Mathematics & Statistics, University of Vermont, Burlington, Vermont 05401, USA.
School of Mathematical Sciences, North Terrace Campus, University of Adelaide, South Australia 5005, Australia.
Phys Rev E. 2017 May;95(5-1):052301. doi: 10.1103/PhysRevE.95.052301. Epub 2017 May 1.
Herbert Simon's classic rich-get-richer model is one of the simplest empirically supported mechanisms capable of generating heavy-tail size distributions for complex systems. Simon argued analytically that a population of flavored elements growing by either adding a novel element or randomly replicating an existing one would afford a distribution of group sizes with a power-law tail. Here, we show that, in fact, Simon's model does not produce a simple power-law size distribution as the initial element has a dominant first-mover advantage, and will be overrepresented by a factor proportional to the inverse of the innovation probability. The first group's size discrepancy cannot be explained away as a transient of the model, and may therefore be many orders of magnitude greater than expected. We demonstrate how Simon's analysis was correct but incomplete, and expand our alternate analysis to quantify the variability of long term rankings for all groups. We find that the expected time for a first replication is infinite, and show how an incipient group must break the mechanism to improve their odds of success. We present an example of citation counts for a specific field that demonstrates a first-mover advantage consistent with our revised view of the rich-get-richer mechanism. Our findings call for a reexamination of preceding work invoking Simon's model and provide an expanded understanding going forward.
赫伯特·西蒙(Herbert Simon)的经典富者愈富模型是最简洁的经验支持机制之一,能够为复杂系统生成具有重尾的规模分布。西蒙从分析上论证了,由添加新元素或随机复制现有元素组成的调味元素群体,将提供具有幂律尾部的群体规模分布。在这里,我们表明,实际上,由于初始元素具有主导的先动优势,西蒙的模型并不会产生简单的幂律规模分布,它将被一个与创新概率倒数成正比的因素所过度代表。第一个群体的规模差异不能被解释为模型的瞬态现象,因此可能比预期大几个数量级。我们展示了西蒙的分析是正确但不完整的,并扩展了我们的替代分析,以量化所有群体的长期排名的可变性。我们发现,首次复制的预期时间是无限的,并展示了一个初始群体如何必须打破机制来提高成功的机会。我们提出了一个特定领域的引文计数示例,该示例显示与我们对富者愈富机制的修正观点一致的先动优势。我们的发现呼吁重新审查先前援引西蒙模型的工作,并提供了扩展的理解。