追踪物理学中的跨领域模因

doi:10.3969/j.issn.0255-8297.2021.03.005

Abstract

Abstract: 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.

Key words: meme, interdisciplinary, community detection, American Physical Society (APS) data set

CLC Number:

G301

ZHOU Yi, YAN Guanghui, LU Binwei, WANG Shan, LI Shikui, WEI Xiang, YANG Shibo, JIN Dan. Tracking Interdisciplinary Memes in Physics[J]. Journal of Applied Sciences, 2021, 39(3): 387-386.

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Tracking Interdisciplinary Memes in Physics

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