Purpose： This paper is an investigation of the effectiveness of the method of clustering biomedical journals through mining the content similarity of journal articles. Design/methodology/approach： 3,265 journals in ...Purpose： This paper is an investigation of the effectiveness of the method of clustering biomedical journals through mining the content similarity of journal articles. Design/methodology/approach： 3,265 journals in Pub Med are analyzed based on article content similarity and Web usage, respectively. Comparisons of the two analysis approaches and a citation-based approach are given.Findings： Our results suggest that article content similarity is useful for clustering biomedical journals, and the content-similarity-based journal clustering method is more robust and less subject to human factors compared with the usage-based approach and the citation-based approach. Research limitations： Our paper currently focuses on clustering journals in the biomedical domain because there are a large volume of freely available resources such as Pub Med and Me SH in this field. Further investigation is needed to improve this approach to fit journals in other domains.Practical implications： Our results show that it is feasible to catalog biomedical journals by mining the article content similarity. This work is also significant in serving practical needs in research portfolio analysis.Originality/value： To the best of our knowledge, we are among the first to report on clustering journals in the biomedical field through mining the article content similarity. This method can be integrated with existing approaches to create a new paradigm for future studies of journal clustering.展开更多
The Chinese urban system is currently experiencing a fundamental shift, as it moves from a size-based hierarchy to a network-based system. Contemporary studies of city networks have tended to focus on economic interac...The Chinese urban system is currently experiencing a fundamental shift, as it moves from a size-based hierarchy to a network-based system. Contemporary studies of city networks have tended to focus on economic interactions without paying sufficient attention to the issue of knowledge flow. Using data on co-authored papers obtained from China Academic Journal Network Publishing Database （CAJNPD） during 2014-2016, this study explores several features of the scientific collaboration network between Chinese mainland cities. The study concludes that： （1） the spatial organization of scientific cooperation amongst Chinese cities is shifting from a jurisdiction-based hierarchical system to a networked system; and （2） several highly intra-connected city regions were found to exist in the network of knowledge, and such regions had more average internal linkages （14.21） than external linkages （8.69）, and higher average internal linkage degrees （14.43） than external linkage degrees （10.43）; and （3） differences existed in terms of inter-region connectivity between the Western, Eastern, and Central China regional networks （the average INCD of the three regional networks were 109.65, 95.81, and 71.88）. We suggest that China should engage in the development of regional and subregional scientific centers to achieve the goal of building an innovative country. Whilst findings reveal a high degree of concentration in those networks - a characteristic which reflects the hierarchical nature of China＇s urban economic structure - the actual spatial distribution of city networks of knowledge flow was found to be different from that of city networks based on economic outputs or population.展开更多
应用基于期刊互引分析的聚类算法对Web of Science中自然科学、社会科学与人文艺术领域八千余种期刊进行聚类分析,将期刊聚类结果与SOOI"专家"分类体系做对比分析,将二者结构的一致部分定义为"学科内核",其余部分则...应用基于期刊互引分析的聚类算法对Web of Science中自然科学、社会科学与人文艺术领域八千余种期刊进行聚类分析,将期刊聚类结果与SOOI"专家"分类体系做对比分析,将二者结构的一致部分定义为"学科内核",其余部分则为"学科外围"。所有学科内核形成了科学结构之网的网上纽结,展示了科学知识的差异性和学科的多样性。学科外围则展现了学科的分化、不同学科的交叉与融合、理论的渗透和方法的移植,以及理论学科和应用学科的相互作用等结构特征。展开更多
基金supported by NIH Intramural Research Program, National Library of Medicine
文摘Purpose： This paper is an investigation of the effectiveness of the method of clustering biomedical journals through mining the content similarity of journal articles. Design/methodology/approach： 3,265 journals in Pub Med are analyzed based on article content similarity and Web usage, respectively. Comparisons of the two analysis approaches and a citation-based approach are given.Findings： Our results suggest that article content similarity is useful for clustering biomedical journals, and the content-similarity-based journal clustering method is more robust and less subject to human factors compared with the usage-based approach and the citation-based approach. Research limitations： Our paper currently focuses on clustering journals in the biomedical domain because there are a large volume of freely available resources such as Pub Med and Me SH in this field. Further investigation is needed to improve this approach to fit journals in other domains.Practical implications： Our results show that it is feasible to catalog biomedical journals by mining the article content similarity. This work is also significant in serving practical needs in research portfolio analysis.Originality/value： To the best of our knowledge, we are among the first to report on clustering journals in the biomedical field through mining the article content similarity. This method can be integrated with existing approaches to create a new paradigm for future studies of journal clustering.
基金National Natural Science Foundation of China,No.41571151,No.41590842,No.71433008
文摘The Chinese urban system is currently experiencing a fundamental shift, as it moves from a size-based hierarchy to a network-based system. Contemporary studies of city networks have tended to focus on economic interactions without paying sufficient attention to the issue of knowledge flow. Using data on co-authored papers obtained from China Academic Journal Network Publishing Database （CAJNPD） during 2014-2016, this study explores several features of the scientific collaboration network between Chinese mainland cities. The study concludes that： （1） the spatial organization of scientific cooperation amongst Chinese cities is shifting from a jurisdiction-based hierarchical system to a networked system; and （2） several highly intra-connected city regions were found to exist in the network of knowledge, and such regions had more average internal linkages （14.21） than external linkages （8.69）, and higher average internal linkage degrees （14.43） than external linkage degrees （10.43）; and （3） differences existed in terms of inter-region connectivity between the Western, Eastern, and Central China regional networks （the average INCD of the three regional networks were 109.65, 95.81, and 71.88）. We suggest that China should engage in the development of regional and subregional scientific centers to achieve the goal of building an innovative country. Whilst findings reveal a high degree of concentration in those networks - a characteristic which reflects the hierarchical nature of China＇s urban economic structure - the actual spatial distribution of city networks of knowledge flow was found to be different from that of city networks based on economic outputs or population.
文摘应用基于期刊互引分析的聚类算法对Web of Science中自然科学、社会科学与人文艺术领域八千余种期刊进行聚类分析,将期刊聚类结果与SOOI"专家"分类体系做对比分析,将二者结构的一致部分定义为"学科内核",其余部分则为"学科外围"。所有学科内核形成了科学结构之网的网上纽结,展示了科学知识的差异性和学科的多样性。学科外围则展现了学科的分化、不同学科的交叉与融合、理论的渗透和方法的移植,以及理论学科和应用学科的相互作用等结构特征。
