Knowledge flow between disciplines is typically measured through citations among publications. In this study, we quantify cross-disciplinary knowledge diffusion from the novel perspective of content by introducing knowledge memes, a special type of knowledge unit. Diffusion cascade is proposed to model the diffusion process of knowledge memes. By taking Medical Informatics (MI) as an exemplary interdisciplinary discipline, we measure the knowledge relationships between it and four related disciplines. The diffusion patterns of cross-disciplinary memes are also identified by analyzing the network structure of the diffusion cascade. The results present the knowledge relationships among disciplines measured by knowledge memes, which are different from those measured by citations. It is shown that preferential attachment takes effect in cross-disciplinary knowledge meme diffusion. In addition, cross-disciplinary knowledge memes generally originate earlier and have higher impact than the memes of MI. This study provides insights into new approaches to quantifying knowledge relationships among disciplines and furthers the understanding of content diffusion mechanisms through measurable knowledge units.

学科之间的知识流通常通过出版物之间的引用来衡量。在这项研究中，我们通过引入知识模因（一种特殊类型的知识单元），从内容的新颖角度来量化跨学科知识的传播。提出了扩散级联模型来模拟知识模因的扩散过程。通过将医学信息学（MI）作为示例性的跨学科学科，我们测量了它与四个相关学科之间的知识关系。通过分析扩散级联的网络结构，还可以确定跨学科模因的扩散模式。结果表明学科之间的知识关系是由知识模因来衡量的，与引用关系所衡量的关系不同。研究表明，优先依恋在跨学科知识模因扩散中起作用。此外，跨学科知识模因通常比MI的模因起源更早，并且影响更大。这项研究提供了对量化学科之间知识关系的新方法的见解，并通过可测量的知识单元进一步增进了对内容传播机制的理解。