Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China.
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
PLoS One. 2022 Sep 28;17(9):e0275192. doi: 10.1371/journal.pone.0275192. eCollection 2022.
The rapid development of modern science nowadays makes it rather challenging to pick out valuable ideas from massive scientific literature. Existing widely-adopted citation-based metrics are not adequate for measuring how well the idea presented by a single publication is developed and whether it is worth following. Here, inspired by traditional X-ray imaging, which returns internal structure imaging of real objects along with corresponding structure analysis, we propose Scientific X-ray, a framework that quantifies the development degree and development potential for any scientific idea through an assembly of 'X-ray' scanning, visualization and parsing operated on the citation network associated with a target publication. We pick all 71,431 scientific articles of citation counts over 1,000 as high-impact target publications among totally 204,664,199 publications that cover 16 disciplines spanning from 1800 to 2021. Our proposed Scientific X-ray reproduces how an idea evolves from the very original target publication all the way to the up to date status via an extracted 'idea tree' that attempts to preserve the most representative idea flow structure underneath each citation network. Interestingly, we observe that while the citation counts of publications may increase unlimitedly, the maximum valid idea inheritance of those target publications, i.e., the valid depth of the idea tree, cannot exceed a limit of six hops, and the idea evolution structure of any arbitrary publication unexceptionally falls into six fixed patterns. Combined with a development potential index that we further design based on the extracted idea tree, Scientific X-ray can vividly tell how further a given idea presented by a given publication can still go from any well-established starting point. Scientific X-ray successfully identifies 40 out of 49 topics of Nobel prize as high-potential topics by their prize-winning papers in an average of nine years before the prizes are released. Various trials on articles of diverse topics also confirm the power of Scientific X-ray in digging out influential/promising ideas. Scientific X-ray is user-friendly to researchers with any level of expertise, thus providing important basis for grasping research trends, helping scientific policy-making and even promoting social development.
现代科学的飞速发展使得从大量科学文献中筛选有价值的思想变得极具挑战性。现有的广泛采用的引文计量指标不足以衡量单一出版物所提出的思想的发展程度及其是否值得关注。在这里，受传统 X 射线成像的启发，它可以提供真实物体的内部结构成像以及相应的结构分析，我们提出了科学 X 射线，这是一种通过在与目标出版物相关的引文网络上进行“X 射线”扫描、可视化和解析的组合，来量化任何科学思想的发展程度和发展潜力的框架。我们从总共涵盖 1800 年至 2021 年 16 个学科的 204,664,199 篇出版物中，挑选了所有 71,431 篇引文计数超过 1,000 的高影响力目标出版物。我们提出的科学 X 射线通过提取“思想树”来重现一个思想如何从最初的目标出版物发展到最新状态，该“思想树”试图在每个引文网络下保留最具代表性的思想流结构。有趣的是，我们观察到，尽管出版物的引文数量可能会无限增加，但这些目标出版物的最大有效思想继承，即思想树的有效深度，不能超过六个跳跃的限制，并且任何任意出版物的思想演化结构都不可避免地落入六个固定模式。结合我们进一步基于提取的思想树设计的发展潜力指数，科学 X 射线可以生动地描述从给定出版物给定思想出发，它还能走多远。科学 X 射线成功地通过获奖论文识别出了 49 个诺贝尔奖主题中的 40 个作为高潜力主题，平均在奖项揭晓前九年。对各种主题的文章的各种试验也证实了科学 X 射线挖掘有影响力/有前途的思想的能力。科学 X 射线对任何专业水平的研究人员都很友好，因此为掌握研究趋势、帮助科学决策甚至促进社会发展提供了重要依据。
