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

Author:

Bornmann Lutz1,de Moya Angeon Felix2

Affiliation:

1. Division for Science and Innovation Studies, Administrative Headquarters of the Max Planck Society, Germany

2. Consejo Superior de Investigaciones Científicas (CSIC), Institute of Public Goods and Policies (IPP), SpainScimago Research Group, Spain

Abstract

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.

Publisher

SAGE Publications

Subject

Library and Information Sciences,Information Systems

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3