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科学进化的剖析

Anatomy of scientific evolution.

作者信息

Yun Jinhyuk, Kim Pan-Jun, Jeong Hawoong

机构信息

Department of Physics, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.

Asia Pacific Center for Theoretical Physics, Pohang, Republic of Korea; Department of Physics, Pohang University of Science and Technology, Pohang, Republic of Korea.

出版信息

PLoS One. 2015 Feb 11;10(2):e0117388. doi: 10.1371/journal.pone.0117388. eCollection 2015.

Abstract

The quest for historically impactful science and technology provides invaluable insight into the innovation dynamics of human society, yet many studies are limited to qualitative and small-scale approaches. Here, we investigate scientific evolution through systematic analysis of a massive corpus of digitized English texts between 1800 and 2008. Our analysis reveals great predictability for long-prevailing scientific concepts based on the levels of their prior usage. Interestingly, once a threshold of early adoption rates is passed even slightly, scientific concepts can exhibit sudden leaps in their eventual lifetimes. We developed a mechanistic model to account for such results, indicating that slowly-but-commonly adopted science and technology surprisingly tend to have higher innate strength than fast-and-commonly adopted ones. The model prediction for disciplines other than science was also well verified. Our approach sheds light on unbiased and quantitative analysis of scientific evolution in society, and may provide a useful basis for policy-making.

摘要

对具有历史影响力的科学技术的探索为洞察人类社会的创新动态提供了宝贵的见解,但许多研究仅限于定性和小规模方法。在此,我们通过对1800年至2008年间大量数字化英语文本语料库进行系统分析来研究科学演变。我们的分析表明,基于其先前使用水平,长期流行的科学概念具有很强的可预测性。有趣的是,一旦早期采用率的阈值哪怕只是略微超过,科学概念在其最终寿命中就可能出现突然飞跃。我们开发了一个机制模型来解释这些结果,表明缓慢但普遍采用的科学技术出人意料地往往比快速且普遍采用的科学技术具有更高的内在强度。该模型对科学以外学科的预测也得到了很好的验证。我们的方法为社会科学演变的无偏定量分析提供了启示,并可能为政策制定提供有用的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ae6/4325003/119aa358b126/pone.0117388.g001.jpg

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