| 翟智慧,李长玲,王庆华,巴秀娜,刘悦.基于雷诺数的学科前沿主题识别——以信息资源管理学科为例[J].数字图书馆论坛,2026,22(2):22~30 |
| 基于雷诺数的学科前沿主题识别——以信息资源管理学科为例 |
| Identifying Disciplinary Research Frontier Topics Based on Reynolds Number: Taking Information Resources Management as an Example |
| 投稿时间：2025-11-14 |
| DOI：10.3772/j.issn .1673-2286.2026.02.003 |
| 中文关键词: 前沿主题；雷诺数；知识流动；前沿识别 |
| 英文关键词: Research Frontier; Reynolds Number; Knowledge Flow; Frontier Identification |
| 基金项目:无 |
| 作者 | 单位 | | 翟智慧 | 山东理工大学信息管理学院 | | 李长玲 | 山东理工大学信息管理学院 | | 王庆华 | 山东理工大学信息管理学院 | | 巴秀娜 | 山东理工大学信息管理学院 | | 刘悦 | 山东理工大学信息管理学院 |
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| 中文摘要: |
| 识别学科研究中的相关前沿主题，有助于把握学科研究现状与趋势，推动学科创新发展。知识流动与流体流动在流动状态和转换过程上具有一定的相似性，均会受到外部因素的影响而发生状态的转变。知识流动过程中，主题因其自身关注度、新颖性、创新性不同，通过被引呈现不同的流动状态。因此，引入区分流体流动状态的雷诺数公式，从关注度、新颖性和创新性3个方面构建模型，识别学科前沿和潜在前沿主题，以信息资源管理学科2015—2024年数据为例进行实证研究。研究结果表明：新兴前沿主题多与生成式人工智能等交叉性的技术知识相关；热点前沿主题多为大数据、社会网络分析等核心专业知识；潜在前沿主题则为数据要素产业等知识。实证证明了雷诺数模型的可行性，可用于识别学科前沿主题。 |
| 英文摘要: |
| Identifying frontier topics in disciplinary research is essential for understanding the current state and trends of research, thereby promoting disciplinary innovation and development. Knowledge flow and fluid flow share similarities in their formation and state transitions, both being influenced by external factors that may trigger changes. In the process of knowledge flow, research topics differ in degree of attention, novelty, and innovativeness, thus exhibiting distinct flow states reflected by citations. Therefore, this paper introduces the Reynolds number formula, which is used to distinguish flow states in fluid mechanics, and constructs a model from the three dimensions of attention, novelty, and innovativeness to identify frontier and potential frontier topics in disciplines. The field of Information Resources Management from 2015 to 2024 is adopted as a case for empirical analysis. The results indicate that emerging frontier topics are closely related to cross-disciplinary technological knowledge such as generative artificial intelligence. Hot frontier topics are primarily situated in core professional domains such as big data and social network analysis. Potential frontier topics pertain to the data-element industry and related knowledge. Empirical research has demonstrated the feasibility of the Reynolds number model, which can be used to identify frontier topics in scientific disciplines. |
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