基于三维引文关联网络的潜在知识流动探测--以基因编辑领域为例

Potential Knowledge Flow Detection from an Integrated Perspective of Three-Dimensional Citations:A Case Study of Gene Editing

在知识经济时代,知识流动在激发知识创新和促进科技发展等方面的价值逐步凸显出来。本文在直引-共被引-耦合三维引文关联网络融合的基础上,对主题关联层面进行映射,对领域内潜在的知识流动进行挖掘。链路预测指标作为特征值,分别应用于构建分类器和回归器。其中,分类器用于预测目前尚未存在、在未来极有可能发生的知识流动;回归器主要用于预测目前链接权重较低的,尚未引起广泛关注、但在未来具有较高链接权重的知识流动。两种预测层面综合互补,可更全面地探测领域内的研究前沿或新兴趋势。利用该思路对当前热门的基因编辑技术领域进行探索研究,得到了该领域中的潜在知识流动和潜在研究的热点,为科研人员选择研究方向提供参考。

In the era of knowledge economy,the value of knowledge flow in stimulating knowledge innovation and promoting scientific and technological development has gradually become more prominent.Based on the fusion of direct-cocitation-coupling citation association,this paper mines the potential knowledge flow in the domain at the subject association level.Indicators of link prediction are used as the feature values to construct the classifier and regressor,respectively.The classifier is used to predict the knowledge flow that is not yet present but is likely to occur in the future.The regressor is mainly used to predict the current knowledge flow with low link weights,which has not attracted widespread attention but has high link weights in the future.The two-layer prediction method is comprehensive and complementary,which can more fully detect research frontiers and emerging trends in the field.Using this idea to explore the currently trending field of gene editing technology,we have obtained the potential knowledge flow and research hotspot in this field,which can serve as a reference for the future research direction for researchers.