Classification of individual articles from all of science by research level

被引：39

作者：

Boyack, Kevin W. ^{[1
]}

Patek, Michael ^{[2
]}

Ungar, Lyle H. ^{[3
]}

Yoon, Patrick ^{[3
]}

Klavans, Richard ^{[4
]}

机构：

[1] SciTech Strategies Inc, Albuquerque, NM 87122 USA

[2] SciTech Strategies Inc, Keene, NH 03431 USA

[3] Univ Penn, Dept Comp & Informat Sci, Philadelphia, PA 19104 USA

[4] SciTech Strategies Inc, Berwyn, PA 19312 USA

来源：

JOURNAL OF INFORMETRICS | 2014年 / 8卷 / 01期

关键词：

Research level; Basic science; Applied science; Multinomial logistic regression model; Article-level classification; JOURNALS;

D O I：

10.1016/j.joi.2013.10.005

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A system of four research levels, designed to classify scientific journals from most applied to most basic, was introduced by Francis Narin and colleagues in the 1970s. Research levels have been used since that time to characterize research at institutional and departmental levels. Currently, less than half of all articles published are in journals that been classified by research level. There is thus a need for the notion of research level to be extended in a way that all articles can be so classified. This article reports on a new model - trained from title and abstract words and cited references - that classifies individual articles by research level. The model covers all of science, and has been used to classify over 25 million articles from Scopus by research level. The final model and set of classified articles are further characterized. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：1 / 12

页数：12

共 18 条

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