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Profiling and predicting the problem-solving patterns in China’s research systems: A methodology of intelligent bibliometrics and empirical insights
Yi Zhang1; Mengjia Wu1; 胡正银2; Robert Ward3; Xue Zhang2; Alan Porter3,4
2020-12
Source PublicationQuantitative Science Studies
Volume0Issue:0Pages:1-28
Abstract

Uncovering the driving forces, strategic landscapes, and evolutionary mechanisms of China’s research systems is attracting rising interest around the globe. One such interest is to understand the problem-solving patterns in China’s research systems now and in the future. Targeting a set of high-quality research articles published by Chinese researchers between 2009 and 2018, and indexed in the Essential Science Indicators database, we developed an intelligent bibliometrics-based methodology for identifying the problem-solving patterns from scientific documents. Specifically, science overlay maps incorporating link prediction were used to profile China’s disciplinary interactions and predict potential cross-disciplinary innovation at a macro level. We proposed a function incorporating word embedding techniques to represent subjects, actions, and objects (SAO) retrieved from combined titles and abstracts into vectors and constructed a tri-layer SAO network to visualize SAOs and their semantic relationships. Then, at a micro level, we developed network analytics for identifying problems and solutions from the SAO network, and recommending potential solutions for existing problems. Empirical insights derived from this study provide clues to understand China’s research strengths and the science policies beneath them, along with the key research problems and solutions Chinese researchers are focusing on now and might pursue in the future.

Other Abstract

Online First:

https://www.mitpressjournals.org/doi/abs/10.1162/qss_a_00100

Language英语
Document Type期刊论文
Identifierhttp://ir.las.ac.cn/handle/12502/11368
Collection中国科学院成都文献情报中心_信息技术部
Corresponding AuthorYi Zhang
Affiliation1.Australian Artificial Intelligence Institute, Faculty of Engineering and Information Technology, University of Technology Sydney
2.中国科学院成都文献情报中心
3.Program in Science, Technology & Innovation Policy (STIP), Georgia Institute of Technology,
4.Search Technology, Inc
First Author Affilication中国科学院文献情报中心
Corresponding Author Affilication中国科学院文献情报中心
Recommended Citation
GB/T 7714
Yi Zhang,Mengjia Wu,胡正银,等. Profiling and predicting the problem-solving patterns in China’s research systems: A methodology of intelligent bibliometrics and empirical insights[J]. Quantitative Science Studies,2020,0(0):1-28.
APA Yi Zhang,Mengjia Wu,胡正银,Robert Ward,Xue Zhang,&Alan Porter.(2020).Profiling and predicting the problem-solving patterns in China’s research systems: A methodology of intelligent bibliometrics and empirical insights.Quantitative Science Studies,0(0),1-28.
MLA Yi Zhang,et al."Profiling and predicting the problem-solving patterns in China’s research systems: A methodology of intelligent bibliometrics and empirical insights".Quantitative Science Studies 0.0(2020):1-28.
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