| 杨金庆,张力.学科交叉视角下新兴主题识别特征分析——以医学信息学为例[J].情报工程,2021,7(4):003-012 |
| 学科交叉视角下新兴主题识别特征分析——以医学信息学为例 |
| The Characteristics Analysis of Emerging Topic Identification from Interdisciplinary Perspective —— A Case Study of Medical Informatics |
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| DOI：10.3772/j.issn.2095-915X.2021.04.001 |
| 中文关键词: 学科交叉；新兴主题；PubMed；医学信息学 |
| 英文关键词: Interdisciplinary; emerging topic; PubMed; medical informatics |
| 基金项目:富媒体数字出版内容组织与知识服务重点实验室开放基金项目 “多模异构数据环境下新兴主题识别及趋势分析”（ZD2020/09-02）。 |
| 作者 | 单位 | | 杨金庆 | 1.武汉大学信息管理学院 武汉 430072；2.富媒体数字出版内容组织与知识服务重点实验室 北京 100038；3.武汉大学图书情报国家级实验教学示范中心 武汉 430072 | | 张力 | 1.武汉大学信息管理学院 武汉 430072；2.富媒体数字出版内容组织与知识服务重点实验室 北京 100038；3.武汉大学图书情报国家级实验教学示范中心 武汉 430072 |
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| 中文摘要: |
| [ 目的/ 意义] 本文以医学信息学为例探析了学科交叉视角下新兴主题识别特征，对于进一步的新兴交叉学科主题分析具有一定的意义。[ 方法/ 过程] 本文首先采用统计分析方法对作者数量、发文量以及资助基金项目进行了历时分析，进一步验证学科交叉主题常规计量维度的适用性；然后运用复杂网络方法分析学科交叉视角下新兴主题的交叉融合新特征以及潜在的网络动态特征。[ 结果/ 结论]实验结果表明：常规性特征发文量、作者数量、资助基金项目数呈指数增长；新兴前阶段学科交叉融合速度较快，篇均医学主题词占比呈显著下降趋势而信息科学呈现快速上升趋势；在新兴前阶段，平均度数（average degree）、聚集系数（convergence）、传递性（transitivity）指标值均呈现增长趋势；同时，三方关系组分析中3 边组合的子图数逐年增加，不同学科主题词对的紧密程度明显增强。 |
| 英文摘要: |
| [Objective/ Significance] This paper explores the characteristics of emerging topics identification from the interdisciplinary perspective with medical informatics as an example, which has some significance for further emerging interdisciplinary topic analysis. [Methods/Process] This paper first employs statistical analysis to analyze the number of authors,publications, and funding programs over time to further verify the applicability of the conventional measurement dimensions of cross-disciplinary topics; and then utilizes a complex network approach to analyze the new features of cross-fertilization and potential network dynamics of emerging topics from a cross-disciplinary perspective. [Results /Conclusions] The experimental results show that: the number of articles, authors, and funding projects of regular features are increasing exponentially; the crossfertilization of disciplines is faster in the pre-emergence stage, and the percentage of medical topic terms in the average article is decreasing significantly while information science is increasing rapidly; in the pre-emergence stage, the average degree,convergence coefficient, and transitivity are increasing. At the same time, the number of subgraphs with 3-sided combinations in the tripartite relational group analysis increased year by year, and the closeness of subject word pairs in different disciplines increased significantly. |
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