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| A Method of Knowledge Evolution Analysis of ESI Research Fronts Based on Knowledge Element Co-occurrence |
| Sun Zhen1, Leng Fuhai2 |
1. Institute of Scientific and Technical Information, Shandong University of Technology, Zibo 255000;
2. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190 |
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Abstract This paper proposes a method for analyzing the knowledge evolution of ESI research fronts based on knowledge element co-occurrence. The method consists of text mining and natural language processing techniques to quantitatively monitor the characteristics of the knowledge flow of research fronts from a microscopic perspective, the findings of which can be used in strategic intelligence research. Based on the documents cited from the main papers comprising the 2016 Research Front report, the knowledge elements related to key innovations from each document were first extracted using the named entity recognition technology and then the centrality and modularity features of the knowledge elements’ co-occurrence networks were analyzed using time series analysis; this was done with the intention of presenting the law of knowledge evolution as it relates to research fronts from the perspective of structural change in scientific knowledge. Through a comparison of the results from the co-occurrence analysis based on keywords and terms, the advanced level and practical applicability of this method were demonstrated using the results of the 2017 Research Front report and authoritative conference papers. This study showed that this method can be used to reveal the microscopic development path and the varying patterns of the research fronts by reorganizing and analyzing the key elements of innovation in the papers.
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Received: 16 January 2018
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