| 陈卫静,王秀明.新兴主题的多维特征测度及中美两国的表现差异研究[J].情报工程,2026,(3):077-092 |
| 新兴主题的多维特征测度及中美两国的表现差异研究 |
| Research on Multi-dimensional Feature of Emerging Topics and Performance Differences between China and the United States |
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| DOI： |
| 中文关键词: 新兴主题；特征测度；多维指标；主题遴选；中美差异 |
| 英文关键词: Emerging Topics; Feature Analysis; Multi-Dimensional Indicators; Topic Selection; Differences Between China and US |
| 基金项目:四川省高等学校人文社会科学重点研究基地——学科发展评价研究中心（成都理工大学）资助项目“研究前沿与学术质量双维度下四川省优势学科的国际竞争力分析”（2024XKFZPJ-Y01）。 |
| 作者 | 单位 | | 陈卫静 | 1. 电子科技大学图书馆 成都 611731；2. 成都理工大学学科发展评价研究中心 成都 610059； | | 王秀明 | 3. 西华大学后勤保障部 成都 610039 |
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| 中文摘要: |
| [目的/意义]从多属性刻画不同领域新兴主题的发展趋势、学术影响、潜在经济社会影响及中美两国的表现差异，为助我国全面宏观把控全球新兴科学技术发展格局提供参考。[方法/过程]基于InCites平台识别的25个新兴主题类别的9250 个新兴主题，构建“发展趋势- 学术影响- 技术转化潜力”的三维特征指标分析体系，宏观分析25个新兴主题类别的指标表现；并采用CRITIC方法确定指标权重，通过计算综合得分，分别遴选25个新兴主题类别中的高质量新兴主题；最后对比分析了中美两国在25 个新兴主题类别上的指标表现差异。[结果/结论]经验证，提出的高质量新兴主题遴选方法具有有效性。发展趋势方面，25个新兴主题类别均呈现较强的新颖性和增长性；学术影响方面，机器学习和人工智能应用、癌症和免疫疗法的高影响研究突出，人工智能与虚拟技术的跨学科研究表现较好，可持续环境修复技术的平均学术影响力最高。技术转化潜力方面，机器学习和人工智能应用、物联网、人工智能和自主系统、癌症和免疫疗法的综合表现较好。中美两国在25 个新兴主题类别上的指标表现差异较大，中国在平均学术影响力、高影响论文产出密度、企业合作论文占比等指标上表现较差，尤其是健康和生物医学领域。[ 局限] 数据源仅考虑了学术论文，未考虑专利数据；研究仅基于已出现的新兴主题，未考虑未来可能出现的新兴主题。 |
| 英文摘要: |
| [Objective/Significance] This paper depicts the development trends, academic impacts and potential socio-economic impacts of emerging topics in different fields, as well as the performance differences between China and the United States.[Methods/Process] Based on 9,250 emerging topics in 25 emerging topic categories identified by InCites, this paper constructs a three-dimensional analysis system of "development trend-academic impact-technology transfer potential" to conduct a macroscopic analysis of the 25 emerging topic categories. Then this paper adopts the CRITIC method to determine the index weight, and calculates the comprehensive score to select the high-quality emerging topics in 25 emerging topic categories. Finally, this paper conducts a comparative analysis on the differences in indicator characteristics between China and the United States in 25 emerging topic categories. [Results/Conclusions] It has been verified that the method for selecting high-quality emerging topics is effective. In terms of development trend, all 25 emerging topic categories show strong novelty and growth potential. In terms of academic impact, Machine learning and AI applications, Cancer and immunotherapy stand out on highimpact research; AI and virtual technologies perform well on interdisciplinary research; Sustainable environmental remediation technologies’ average academic impact is the highest. In terms of the technology transfer potential, Machine learning and AI applications, IoT, AI, and autonomous systems, Cancer and immunotherapy, these three emerging topic categories perform well.
There are significant differences in indicator characteristics between China and the United States in 25 emerging topic categories.China performs poorly in indicators such as average academic impact, the density of high-impact paper output, and the proportion of enterprise collaborative papers, especially in the fields of health and biomedicine. [Limitations] Analysis data only considered papers, did not include patents. Analysis only based on existing emerging topics, without accounting for emerging topics that may occur in the future. |
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