Hot and cold spots in the US research: A spatial analysis of bibliometric data on the institutional level

被引:16
作者
Bornmann, Lutz [1 ]
Angeon, Felix de Moya [2 ,3 ]
机构
[1] Adm Headquarters Max Planck Soc, Div Sci & Innovat Studies, Hofgartenstr 8, D-80539 Munich, Germany
[2] CSIC, Inst Publ Goods & Policies IPP, Madrid, Spain
[3] Scimago Res Grp, Madrid, Spain
关键词
Bibliometrics; getisord; spatial proximity; UNIVERSITIES; NETWORKS; SCIENCE;
D O I
10.1177/0165551518782829
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Spatial bibliometrics addresses the spatial aspects of scientific research activities. In this case study, we use the Getis-Ord G* i (d) statistic for bibliometric data on US institutions to identify hot spots of institutions on a map publishing many high-impact papers. The study is based on a dataset with performance data (proportion and number of papers belonging to the 10% most frequently cited papers) and geo-coordinates for all institutions in the United States from the SCImago group (and Scopus). The Getis-Ord Gi* statistic returns, for each institution on a map, a z score. Higher z scores point to intense clustering of institutions, which have published a large proportion or number of highly cited papers (hot spots). The US maps, which we generate as examples in this study, point to four regions. These regions can be labelled as hot spots: around San Francisco, Los Angeles, Boston and Washington, DC. The empirical focus on institutional hot spots in a country using bibliometric data is of specific importance for science policy, because geospatial proximity is shown as an important factor for innovation processes.
引用
收藏
页码:84 / 91
页数:8
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