论文标题
Google Scholar引用的全球分布：基于规模的基于机构的分析
Global Distribution of Google Scholar Citations: A Size-independent Institution-based Analysis
论文作者
论文摘要
目前针对大学或研究组织的基于绩效排名的大多数可用方案，例如，Quacarelli Symonds（QS），Times高等教育（The），上海大学，基于世界大学的所有研究（ARWU），都使用各种标准，这些标准包括生产力，引用，引用，奖励，奖励，声誉等，而Leiden和Scimogo仅使用Biblioptrimits指标。上述案例中的研究绩效评估是基于科学或Scopus Web的书目计量数据，这些数据是商业上可用的数据库。覆盖范围包括同行评审的期刊和会议记录。另一方面，Google Scholar（GS）为获得网络上可用的论文引用提供了一种免费的开放替代方案（尽管尚不清楚确切地涵盖了哪些期刊。）引用是从网络中自动收集的，并在Google Scholar Citations（GSC）下自动添加到了自我创建的个人作者资料（GSC）。西班牙网络计量量表实验室使用此数据在2016年创建了4000多家机构的排名列表，这是基于每个组织中排名前10位的个人GSC配置文件的引用。 （GSC出于文本中解释的原因不包括最重要的论文；简单的选择过程使网络对称实验室所声称的排名列表大小无关）。使用此数据（透明排名TR，2016年），我们发现了GS-TR引用的区域和国家明智的分布。大小独立排名的列表分为每家400个机构的十分位，以及每个十分位数获得的每个国家的机构数量和引用。我们测试GS TR与前20个机构的其他排名方案之间的机构等级之间的相关性。
Most currently available schemes for performance based ranking of Universities or Research organizations, such as, Quacarelli Symonds (QS), Times Higher Education (THE), Shanghai University based All Research of World Universities (ARWU) use a variety of criteria that include productivity, citations, awards, reputation, etc., while Leiden and Scimago use only bibliometric indicators. The research performance evaluation in the aforesaid cases is based on bibliometric data from Web of Science or Scopus, which are commercially available priced databases. The coverage includes peer reviewed journals and conference proceedings. Google Scholar (GS) on the other hand, provides a free and open alternative to obtaining citations of papers available on the net, (though it is not clear exactly which journals are covered.) Citations are collected automatically from the net and also added to self created individual author profiles under Google Scholar Citations (GSC). This data was used by Webometrics Lab, Spain to create a ranked list of 4000+ institutions in 2016, based on citations from only the top 10 individual GSC profiles in each organization. (GSC excludes the top paper for reasons explained in the text; the simple selection procedure makes the ranked list size-independent as claimed by the Cybermetrics Lab). Using this data (Transparent Ranking TR, 2016), we find the regional and country wise distribution of GS-TR Citations. The size independent ranked list is subdivided into deciles of 400 institutions each and the number of institutions and citations of each country obtained for each decile. We test for correlation between institutional ranks between GS TR and the other ranking schemes for the top 20 institutions.
