经验数据中的马太效应
The Matthew effect in empirical data
摘要：
马太效应描述了一种现象，即在社会中，富人往往会变得更富有，而有权势的人则会变得更有权势。它与网络科学中的优先连接概念密切相关，其中连接更多的节点注定要在未来获得比辅助节点多得多的链接。累积优势和成功-面包-成功也都描述了这样一个事实，即优势往往会产生更多的优势。这一概念是经验数据中许多幂律和缩放行为的背后，也是社会科学和自然科学自组织的核心。在这里，我们审查的方法来衡量优先附件的实证数据，以及观察的马太效应的模式，科学合作，社会技术和生物网络，传播的引文，出现的科学进步和影响，职业寿命，常见的英语单词和短语的演变，以及在教育和大脑发育。我们还讨论了马太效应是否是由于机会或优化，例如在社会系统中的同质性或在技术系统中的功效，我们概述了未来研究的可能方向。
英文摘要：
The Matthew effect describes the phenomenon that in societies the rich tend to get richer and the potent even more powerful. It is closely related to the concept of preferential attachment in network science, where the more connected nodes are destined to acquire many more links in the future than the auxiliary nodes. Cumulative advantage and success-breads-success also both describe the fact that advantage tends to beget further advantage. The concept is behind the many power laws and scaling behaviour in empirical data, and it is at the heart of self-organization across social and natural sciences. Here we review the methodology for measuring preferential attachment in empirical data, as well as the observations of the Matthew effect in patterns of scientific collaboration, socio-technical and biological networks, the propagation of citations, the emergence of scientific progress and impact, career longevity, the evolution of common English words and phrases, as well as in education and brain development. We also discuss whether the Matthew effect is due to chance or optimisation, for example related to homophily in social systems or efficacy in technological systems, and we outline possible directions for future research.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
