TigerGraph, 3 Twin Dolphin Dr, St. 225, Redwood City, CA, 94065, USA.
Knowledge Lab, University of Chicago, 1155 E. 60th Street #211, Chicago, IL, 60637, USA.
Nat Commun. 2023 Mar 24;14(1):1641. doi: 10.1038/s41467-023-36741-4.
We investigate the degree to which impact in science and technology is associated with surprising breakthroughs, and how those breakthroughs arise. Identifying breakthroughs across science and technology requires models that distinguish surprising from expected advances at scale. Drawing on tens of millions of research papers and patents across the life sciences, physical sciences and patented inventions, and using a hypergraph model that predicts realized combinations of research contents (article keywords) and contexts (cited journals), here we show that surprise in terms of unexpected combinations of contents and contexts predicts outsized impact (within the top 10% of citations). These surprising advances emerge across, rather than within researchers or teams-most commonly when scientists from one field publish problem-solving results to an audience from a distant field. Our approach characterizes the frontier of science and technology as a complex hypergraph drawn from high-dimensional embeddings of research contents and contexts, and offers a measure of path-breaking surprise in science and technology.
我们研究了科学技术领域的影响力与惊人突破之间的关联程度,以及这些突破是如何产生的。要在科学技术领域识别突破,需要使用能够区分大规模预期进展和意外进展的模型。我们利用生命科学、物理科学和已获专利发明领域的数千万篇研究论文和专利,使用一种能够预测研究内容(文章关键词)和背景(引用期刊)实际组合的超图模型,结果表明,内容和背景的意外组合所带来的意外可以预测巨大的影响力(在前 10%的引用中)。这些令人惊讶的进展跨越了研究人员或团队的界限,而不是局限于某一个或某一组人——最常见的情况是,来自一个领域的科学家将解决问题的成果发表给来自遥远领域的读者。我们的方法将科学技术的前沿描述为一个复杂的超图,它是从研究内容和背景的高维嵌入中提取出来的,并提供了一种衡量科学技术领域突破性惊喜的方法。