Research on the Knowledge Feature Identification of Disruptive Technologies from Its Backward Scientific Citations:Taking the Field of Genetic Engineering as an Example
[Purpose/Significance]Disruptive technology plays an important supporting role in the political,eco-nomic,and social security of a country.Accurately identifying the features of disruptive technologies is of great signif-icance for predicting the direction of technological innovation and optimizing the national innovation strategic layout.[Method/Process]This paper focuses on the ability of the knowledge features of patents'scientific references(i.e.,backward scientific citations)to foresee disruptive technologies.Firstly,the knowledge features of backward scientific citations are quantified from two aspects:the knowledge content of the cited scientific papers and the knowledge as-sociation between citing and cited literature.Then,the stepwise regression method is used to preliminarily identify the candidate features significantly related to the degree of patent innovation.Finally,machine learning methods and the Shapley additional explanations(SHAP)model are introduced to deeply analyze the correlation between the knowl-edge features of backward scientific citations and the degree of patent innovation,and thus identify the critical knowl-edge features of backward scientific citations that can predict disruptive technologies.[Result/Conclusion]The empir-ical analysis results in the field of genetic engineering indicate that,except for the novelty of cited papers'knowledge combination,there is a significant nonlinear correlation between other knowledge features of scientific references and the degree of patent innovation.Within a certain threshold range,the knowledge features of disruptive technologies'backward scientific citations may exhibit low knowledge impact and knowledge element diversity,high knowledge interdisciplinary,as well as long publication time interval and great knowledge correlation with citing patents.
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