综述

新兴研究主题识别方法研究进展与前瞻

  • 许海云 ,
  • 龚兵营 ,
  • 杨俊浩 ,
  • 胡晓阳 ,
  • 王超 ,
  • 陈亮
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  • 1 山东理工大学管理学院 淄博 255000;
    2 中国科学技术信息研究所 北京 100038
许海云,教授,博士,博士生导师,E-mail:xuhaiyunnemo@gmail.com;龚兵营,硕士研究生;杨俊浩,硕士研究生;胡晓阳,硕士研究生;王超,副教授,博士,硕士生导师;陈亮,副研究员,博士,硕士生导师。

收稿日期: 2024-02-04

  修回日期: 2024-08-14

  网络出版日期: 2025-02-11

基金资助

本文系国家自然科学基金项目“基于弱信号时效网络演化分析的变革性科技创新主题早期识别方法研究”(项目编号:72274113)和山东省自然科学基金“基于弱信号分析的变革性创新主题早期识别方法研究”(项目编号:ZR202111130115)研究成果之一。

Research Progress and Prospect of Emerging Research Topic Identification Methods

  • Xu Haiyun ,
  • Gong Bingying ,
  • Yang Junhao ,
  • Hu Xiaoyang ,
  • Wang Chao ,
  • Chen Liang
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  • 1 Business School, Shandong University of Technology, Zibo 255000;
    2 Institute of Scientific and Technical Information of China, Beijing 100038

Received date: 2024-02-04

  Revised date: 2024-08-14

  Online published: 2025-02-11

Supported by

This work is supported by the National Natural Science Foundation of China project titled “Early Recognition Method of Transformative Scientific and Technological Innovation Topics based on Weak Signal Temporal Network Evolution analysis” (Grant No. 72274113), the Natural Science Foundation of Shandong Province project titled “Early Recognition Method of Transformational Innovation Topics Using Weak Signal Analysis” (Grant No. ZR202111130115).

摘要

[目的/意义] 在数据量剧增和技术快速发展的背景下,借助数智技术实现新兴研究主题更精准的早期识别具有重要意义。梳理相关文献,为新兴研究主题识别方法研究,提供具有更高精准度和多个不同视角下的方法参照及前瞻思考。[方法/过程] 以Web of Science核心数据库和CNKI为文献来源,首先辨析新兴研究主题及其相关概念,梳理新兴研究主题识别研究所涉多源数据,之后重点综述新兴研究主题的识别方法,关注当前科技情报分析领域应用度较低但极具前景的方法和理论视角,从而对识别方法进行梳理总结,最后,提出新兴研究主题识别未来可行性方向。[结果/结论] 新兴研究主题一直是科技情报的前沿热点课题,对其特征的解析日益清晰,识别方法迭代快速。但当前研究中仍存在数据类型单一,先进识别方法与工具欠缺等问题。未来需要拓展理论视角,加持数智技术,覆盖新兴研究主题更多维度,并形成结合专家智慧的新兴研究主题识别方法研究,提高新兴研究主题识别的准确率和召回率。

本文引用格式

许海云 , 龚兵营 , 杨俊浩 , 胡晓阳 , 王超 , 陈亮 . 新兴研究主题识别方法研究进展与前瞻[J]. 图书情报工作, 2025 , 69(3) : 135 -150 . DOI: 10.13266/j.issn.0252-3116.2025.03.012

Abstract

[Purpose/Significance] With the rapid growth of data volumes and technological advancements, leveraging intelligent technologies for earlier and more precise identification of emerging research topics is of great importance. This paper reviews relevant literature to provide a more precise and multi-perspectival methodological reference for future research on the emerging research topics identification. [Method/Process] Using the Web of Science Core Collection and CNKI as data sources, this study first clarified emerging research topics and related concepts, summarized the multi-source data used in the research. It then focused on reviewing the identification methods, emphasizing those with currently low application but high potential in science and technology intelligence analysis, and provided a comprehensive overview. Finally, the paper proposed feasible directions for the emerging research topic identification. [Result/Conclusion] Emerging research topics have always been a frontier hotspot in scientific intelligence, with increasingly clear characterizations and rapidly iterating identification methods. However, current research faces challenges such as single data types and a lack of advanced identification methods and tools. Future research needs to expand theoretical perspectives, enhance the use of intelligent technologies, cover more dimensions of emerging research topics, and integrate expert knowledge to improve the accuracy and recall rate of emerging research topic identification.

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