以美国物理学会旗下期刊2000—2019年发表的论文和Web of Science论文摘要为基础，用模因短语刻画知识，构建模因关系网络并引入跨学科测度Rao-Stirling指数以计算模因的跨领域分数，从而追踪物理学中的跨领域模因。分别从网络拓扑结构指标、跨领域测度指标和专业术语对比3个方面进行验证，证明了所提的模因关系网络和模因的跨领域分数可以有效反映知识在不同领域间的扩散现象。
Based on the papers published in American Physical Society (APS) journals from 2000 to 2019 and abstracts from Web of Science, we firstly use meme phrases to describe knowledge and construct meme correlation network (MCN) to track interdisciplinary memes. And then we use Rao-Stirling index to calculate the interdisciplinary scores of memes, and track interdisciplinary memes in physics. The verification experiment was carried out from three perspectives of network topology index, interdisciplinary measurement index and professional terminology comparison. It proved that the meme correlation network (MCN) and the interdisciplinary score of memes in this paper can effectively reflect the diffusion of knowledge in different domains.
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