排名(信息检索)
劣势
主题(文档)
分类
机构
领域(数学)
计算机科学
职位(财务)
数据科学
期刊排名
社会学
情报检索
社会科学
业务
图书馆学
人工智能
数学
引用
财务
纯数学
作者
Lutz Bornmann,Félix de Moya Anegón,Rüdiger Mutz
摘要
Using data compiled for the SCImago Institutions Ranking, we look at whether the subject area type an institution (university or research‐focused institution) belongs to (in terms of the fields researched) has an influence on its ranking position. We used latent class analysis to categorize institutions based on their publications in certain subject areas. Even though this categorization does not relate directly to scientific performance, our results show that it exercises an important influence on the outcome of a performance measurement: Certain subject area types of institutions have an advantage in the ranking positions when compared with others. This advantage manifests itself not only when performance is measured with an indicator that is not field‐normalized but also for indicators that are field‐normalized.
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