Content-based author co-citation analysis

被引：167

作者：

Jeong, Yoo Kyung ^{[1
]}

Song, Min ^{[1
]}

Ding, Ying ^{[2
]}

机构：

[1] Yonsei Univ, Dept Lib & Informat Sci, Seoul 120749, South Korea

[2] Indiana Univ, Dept Informat & Lib Sci, Bloomington, IN USA

来源：

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

基金：

新加坡国家研究基金会;

关键词：

Author co-citation analysis; Citation content analysis; Bibliometrics; Information science; Citation analysis; ALL-AUTHOR; INTELLECTUAL STRUCTURE; CITATION ANALYSIS; MANAGEMENT FIELD; PROXIMITY; WEB; PUBLICATIONS; 1ST;

D O I：

10.1016/j.joi.2013.12.001

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Author co-citation analysis (ACA) has long been used as an effective method for identifying the intellectual structure of a research domain, but it relies on simple co-citation counting, which does not take the citation content into consideration. The present study proposes a new method for measuring the similarity between co-cited authors by considering author's citation content. We collected the full-text journal articles in the information science domain and extracted the citing sentences to calculate their similarity distances. We compared our method with traditional ACA and found out that our approach, while displaying a similar intellectual structure for the information science domain as the other baseline methods, also provides more details about the sub-disciplines in the domain than with traditional ACA. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：197 / 211

页数：15

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