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关系网络视角下新兴技术识别研究进展

  • 刘盼盼 ,
  • 王丽
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  • 1. 中国科学院文献情报中心 北京 100190;
    2. 中国科学院大学经济与管理学院图书情报与档案管理系 北京 100190
刘盼盼,硕士研究生。

收稿日期: 2021-12-05

  修回日期: 2022-01-19

  网络出版日期: 2022-06-18

基金资助

本文系国家科技图书文献中心NSTL项目"国家重大科技战略问题情报研究"(项目编号:2021XM59)研究成果之一。

Research Progress of Emerging Technology Identification from the Perspective of Relational Network

  • Liu Panpan ,
  • Wang Li
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  • 1. National Science Library, Chinese Academy of Sciences, Beijing 100190;
    2. Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190

Received date: 2021-12-05

  Revised date: 2022-01-19

  Online published: 2022-06-18

摘要

[目的/意义] 新兴技术识别有助于国家、企业等把握技术前沿、发现技术机会、抢占市场先机、创造社会价值。梳理新兴技术识别的研究进展,以期为新兴技术识别研究提供参考。[方法/过程] 在明确新兴技术概念和特征的基础上,详细介绍基于关系网络的新兴技术识别方法,并从新兴技术识别的网络节点、网络关系、测度指标进行总结,对未来新兴技术识别研究提出建议。[结果/结论] 基于关系网络的新兴技术识别方法包括基于引用关系、共现关系以及相似度关系的方法,新兴技术识别的网络节点主要来自论文和专利数据,现有指标体系包括文献计量学指标和网络结构特征指标。未来,新兴技术识别研究可以从丰富数据源、网络关系融合、测度指标等方面进行改进;同时,重点加强对新兴技术识别中多源数据和多元关系的融合网络的探索。

本文引用格式

刘盼盼 , 王丽 . 关系网络视角下新兴技术识别研究进展[J]. 图书情报工作, 2022 , 66(11) : 139 -150 . DOI: 10.13266/j.issn.0252-3116.2022.11.015

Abstract

[Purpose/Significance] Emerging technology identification helps countries and enterprises to grasp the technological frontier, discover technological opportunities, seize market opportunities and create social value. This paper reviews the research progress of emerging technology identification, and provides a reference for the study of emerging technology identification. [Method/Process] On the basis of clarifying the concepts and characteristics of emerging technology, this paper introduced the identification methods of emerging technologies based on relational networks in detail, summarized the network nodes, network relationships and measurement indicators of emerging technology identification, and made recommendations for the future study of emerging technology identification. [Result/Conclusion] The identification methods of emerging technology based on relational networks include the methods based on citation relationships, co-occurrence relationships, and similarity relationships. The network nodes of emerging technology identification are mainly from papers and patents data. The existing indicator system includes bibliometric indicators and network structure characteristic indicators. In the future, the study of emerging technology identification can be improved from the aspects of enriching data sources, integrating network relationships and measurement indicators. At the same time, the exploration of fusion network of multi-source data and multiple relationships in emerging technology identification should be strengthened.

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