Data from: Anatomy of scientific evolution

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.探寻具有历史影响力的科学与技术，可为洞悉人类社会的创新动态提供极为宝贵的洞见，但现有诸多研究多局限于定性分析与小规模研究范式。本文通过对1800年至2008年间的大规模数字化英文文本语料库开展系统性分析，探究科学演化规律。研究结果显示，基于科学概念的前期使用水平，可对其长期存续性实现较高精度的预测。值得注意的是，即便仅略微突破早期采用率阈值，科学概念的最终存续周期便可能出现突发性跃升。我们构建了一套机制模型以阐释上述现象，结果表明：缓慢却普遍被采用的科学与技术，其固有强度竟高于快速且普遍被采用的同类成果。该模型针对非科学领域的预测也得到了良好验证。本研究为社会层面科学演化的无偏定量分析提供了新的研究路径，或可为政策制定提供有益的参考依据。