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Identifying and tracking scientific and technological knowledge memes from citation networks of publications and patents

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Abstract

Knowledge memes are the cultural equivalent of genes that play an important role in the evolution of knowledge. In this paper, we are trying to identify and tracking scientific and technological knowledge memes, and infer the relationship between science and technology at micro-level. A new carbon nanomaterial—graphene is taken as an example, and publications and patents are used as data sources for the representation of science and technology. Citation networks of publications and patents are constructed, on which a knowledge meme discovery algorithm is used, in order to identify memes that play a key role in the evolution of scientific and technological knowledge. Then the diffusion and co-occurrence of knowledge memes are shown, and a word embedding model is used to track the semantic change of the memes. The research could provide guidance for promoting knowledge innovation and making research policy.

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Acknowledgements

This work is partially supported by grant from National Natural Science Foundation of China (No. 71704019), Postdoctoral Science Foundation of China (Nos. 2015M581337, 2016T90224), and the Fundamental Research Funds for the Central Universities.

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  1. Institute of Science of Science and S&T Management, Dalian University of Technology, Dalian, 116024, China

    Xiaoling Sun & Kun Ding

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  1. Xiaoling Sun
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  2. Kun Ding
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Correspondence to Xiaoling Sun.

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Sun, X., Ding, K. Identifying and tracking scientific and technological knowledge memes from citation networks of publications and patents. Scientometrics 116, 1735–1748 (2018). https://doi.org/10.1007/s11192-018-2836-1

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