A co-citation approach to the analysis on the interaction between scientific and technological knowledge

Xi Chen, Jin Mao and Gang Li

Journal of Informetrics, 2024, vol. 18, issue 3

Abstract: A systematic understanding of the interaction between science and technology is beneficial for innovation policies aimed at improving the utilization of science to advance technological development. Traditional approaches primarily focus on direct citation-based linkages, often overlooking the complex, evolving nature of the interaction between scientific and technological knowledge (S&T knowledge interaction). To address this issue, we proposed a novel methodological framework utilizing co-citations between patents and papers, offering a more comprehensive insight into the S&T knowledge interaction. First, we measured the linkage between scientific and technological knowledge based on co-citations between patents and papers. Then, we identified interaction communities and analyzed their evolution. This method not only captures the potential linkages between patents and papers, but also reveals consolidated interactions and rapid changes in S&T knowledge interaction. The results highlight distinct phases in the evolution of S&T knowledge interaction, which are instrumental for understanding how S&T knowledge interaction evolve, especially in rapidly advancing fields like genetic engineering. The insights gained are crucial for academics and practitioners in anticipating future trends and navigating the evolving landscape of science and technology.

Keywords: Patents; Science and technology interaction; Dynamic network analysis; Co-citation analysis (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:18:y:2024:i:3:s1751157724000610

DOI: 10.1016/j.joi.2024.101548

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