基于引文曲线拟合的新兴技术主题的突破性预测——以干细胞领域为例

doi:10.13266/j.issn.0252-3116.2020.05.011

图书情报工作 ›› 2020, Vol. 64 ›› Issue (5): 100-113.DOI: 10.13266/j.issn.0252-3116.2020.05.011

基于引文曲线拟合的新兴技术主题的突破性预测——以干细胞领域为例

曹艺文^1,2, 许海云^1,3, 武华维^1,2, 罗瑞^1,2

1. 中国科学院成都文献情报中心成都 610041;
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;
3. 中国科学技术信息研究所北京 100038

收稿日期:2019-05-15 修回日期:2019-09-20 出版日期:2020-03-05 发布日期:2020-03-05
通讯作者: 许海云(ORCID:0000-0002-7453-3331),副研究员,博士,通讯作者,E-mail:xuhy@clas.ac.cn
作者简介:曹艺文(ORCID:0000-0002-2439-1101),硕士研究生;武华维(ORCID:0000-0001-6969-407X),博士研究生;罗瑞(ORCID:0000-0002-5234-8901),硕士研究生。
基金资助:
本文系国家自然科学基金项目"基于科学-技术主题关联分析的创新演化路径识别方法研究"（项目编号：71704170）和中国科学院十三五信息化项目"面向干细胞领域知识发现的科研信息化应用"（项目编号：XXH13506）研究成果之一。

Study on Radical Innovation Prediction to Emerging Technology Topics Based on Citation Curve Fitting——Taking the Field of Stem Cells as an Example

Cao Yiwen^1,2, Xu Haiyun^1,3, Wu Huawei^1,2, Luo Rui^1,2

1. Chengdu Documentation and Information Center, Chinese Academy of Sciences, Chengdu 610041;
2. Department of Library, Information and Archives Management, School of Economic and Management, University of Chinese Academy of Sciences, Beijing 100190;
3. Institute of Scientific and Technical Information of China(ISTIC), Beijing 100038

Received:2019-05-15 Revised:2019-09-20 Online:2020-03-05 Published:2020-03-05

摘要/Abstract

摘要： [目的/意义] 通过对新兴技术主题的引文曲线进行拟合分析，提炼和归纳引文曲线的主要类型和特征，以期能为微观层面突破性创新主题预测方法的研究提供参考。[方法/过程] 首先提出利用引文曲线追踪感知新兴技术主题形成突破性创新的假设，并提出跃迁指数的概念和计量方法，从知识跃迁和持续增长两个维度总结识别突破性创新的标准并构建突破性识别的方法模型。其次利用新兴技术主题发文的时序被引数据构建引文曲线并进行拟合分析，实现对不同主题包含的引文曲线的类型分类，提炼引文曲线的主要特征进行突破性预测。[结果/结论] 新兴技术主题引文曲线的特征包括：近期持续增长；近期持续下降；生命周期短；相近年份变化趋势一致。根据突破性创新的识别标准，如果引文曲线跃迁次数多、跃迁幅度大，最高被引峰值出现时间较晚，并且在近期保持高被引且持续稳定或快速增长，则新兴技术主题具有成为突破性创新的潜力。结合领域专家对预测结果的评估以及不同新兴技术主题的研究进展，验证了利用引文曲线可以有效预测新兴技术主题的突破性。

关键词: 突破性创新, 技术预测, 引文曲线, 新兴技术主题

Abstract: [Purpose/significance] Through the fitting analysis of the citation curves of emerging technology topics, this paper refined and summarized the main types and characteristics of the citation curves, in order to provide a useful reference for the study of prediction methods for radical innovation topics at the micro level.[Method/process] Firstly, the hypothesis of using citation curves to trace the emerging technology topics to produce radical innovation was proposed and the concept and measurement method of the transition index were proposed. The criteria of predicting radical innovation were summarized and the method model of radical innovation identification was constructed from the two dimensions of knowledge transition and continuous growth. Then used the time slices cited data of each emerging technology topic to construct the citation curves, classify and summarize the types and characteristics of citation curves of different emerging technology topics.[Result/conclusion] The citation curves of emerging technology topics includes four types:continuous growth in the near future; continuous decline in the near future; short life cycle; consistent trends in similar years. According to the identification criteria of radical innovation, the citation curves have the potential to become radical innovation if they have many transitions and a large transition range, and the highest citation peak occurs later, and maintains a high citation rate in the near future with a sustained stable or rapid growth. Combined with the assessment of the prediction results by domain experts and the research progress of different emerging technology topics, it is verified that the citation curve fitting analysis can effectively predict the breakthrough of emerging technology topics.

Key words: radical innovation, technical forecast, citation curve, emerging technology topic

中图分类号:

G250

曹艺文, 许海云, 武华维, 罗瑞. 基于引文曲线拟合的新兴技术主题的突破性预测——以干细胞领域为例[J]. 图书情报工作, 2020, 64(5): 100-113.

Cao Yiwen, Xu Haiyun, Wu Huawei, Luo Rui. Study on Radical Innovation Prediction to Emerging Technology Topics Based on Citation Curve Fitting——Taking the Field of Stem Cells as an Example[J]. LIS, 2020, 64(5): 100-113.

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基于引文曲线拟合的新兴技术主题的突破性预测——以干细胞领域为例

Study on Radical Innovation Prediction to Emerging Technology Topics Based on Citation Curve Fitting——Taking the Field of Stem Cells as an Example

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