A Bibliometric Approach for Department-Level Disciplinary Analysis and Science Mapping of Research Output Using Multiple Classification Schemes

Pitambar Gautam
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引用次数: 6

Abstract

This study describes an approach for comparative bibliometric analysis of scientific publications related to (i) individual or several departments comprising a university, and (ii) broader integrated subject areas using multiple disciplinary schemes. It uses a custom dataset of scientific publications (ca. 15,000 articles and reviews, published during 2009-2013, and recorded in the Web of Science Core Collections) with author affiliations to the research departments, dedicated to science, technology, engineering, mathematics, and medicine (STEMM), of a comprehensive university. The dataset was subjected, at first, to the department level and discipline level analyses using the newly available KAKEN-L3 classification (based on MEXT/JSPS Grants-in-Aid system), hierarchical clustering, correspondence analysis to decipher the major departmental and disciplinary clusters, and visualization of the department-discipline relationships using two-dimensional stacked bar diagrams. The next step involved the creation of subsets covering integrated subject areas and a comparative analysis of departmental contributions to a specific area (medical, health and life science) using several disciplinary schemes: Essential Science Indicators (ESI) 22 research fields, SCOPUS 27 subject areas, OECD Frascati 38 subordinate research fields, and KAKEN-L3 66 subject categories. To illustrate the effective use of the science mapping techniques, the same subset for medical, health and life science area was subjected to network analyses for co-occurrences of keywords, bibliographic coupling of the publication sources, and co-citation of sources in the reference lists. The science mapping approach demonstrates the ways to extract information on the prolific research themes, the most frequently used journals for publishing research findings, and the knowledge base underlying the research activities covered by the publications concerned.
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基于多分类方案的部门级学科分析和科研成果科学映射的文献计量学方法
本研究描述了一种对科学出版物进行比较文献计量分析的方法,这些出版物涉及(i)大学的单个或多个系,以及(ii)使用多学科方案的更广泛的综合学科领域。它使用一个自定义的科学出版物数据集(2009-2013年期间发表的约15,000篇文章和评论,并记录在Web of Science核心馆藏中),作者隶属于一所综合性大学的科学、技术、工程、数学和医学(STEMM)研究部门。首先,使用最新的KAKEN-L3分类(基于MEXT/JSPS Grants-in-Aid系统)对数据集进行部门级和学科级分析,分层聚类,对应分析以解读主要部门和学科集群,并使用二维堆叠条形图可视化部门-学科关系。下一步涉及创建涵盖综合学科领域的子集,并使用几个学科计划对部门对特定领域(医学、健康和生命科学)的贡献进行比较分析:基本科学指标(ESI) 22个研究领域,SCOPUS 27个学科领域,OECD Frascati 38个从属研究领域,以及KAKEN-L3 66个学科类别。为了说明科学制图技术的有效使用,对医学、健康和生命科学领域的同一子集进行了关键词共现、出版物来源的书目耦合以及参考文献列表中来源的共引的网络分析。科学制图方法展示了如何提取有关高产研究主题、发表研究成果最常用的期刊以及有关出版物所涵盖的研究活动的基础知识的信息。
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来源期刊
Journal of Contemporary Eastern Asia
Journal of Contemporary Eastern Asia Social Sciences-Communication
CiteScore
1.60
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