Visualizing the intellectual structure of information science (2006-2015): Introducing author keyword coupling analysis

被引:65
作者
Yang, Siluo [1 ,3 ]
Han, Ruizhen [1 ]
Wolfram, Dietmar [2 ]
Zhao, Yuehua [2 ]
机构
[1] Wuhan Univ, Sch Informat Management, Wuhan 430072, Peoples R China
[2] Univ Wisconsin, Sch Informat Studies, POB 413, Milwaukee, WI 53201 USA
[3] Xiangtan Univ, Sch Publ Management, Xiangtan 411105, Peoples R China
关键词
Author keyword coupling analysis; Information science; Author bibliographic coupling analysis; Bibliometric mapping; RESEARCH-FRONT; COCITATION ANALYSIS; CITATION ANALYSIS; NETWORKS; BASE; WEB;
D O I
10.1016/j.joi.2015.12.003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We introduce the author keyword coupling analysis (AKCA) method to visualize the field of information science (2006-2015). We then compare the AKCA method with the author bibliographic coupling analysis (ABCA) method in terms of first- and all-author citation counts. We obtain the following findings: (1) The AKCA method is a new and feasible method for visualizing a discipline's structure, and the ABCA and AKCA methods have their respective strengths and emphases. The relation within the ABCA method is based on the same references (knowledge base), whereas that within the AKCA method is based on the same keywords (lexical linguistic). The AKCA method appears to provide a less detailed picture, and more uneven sub-areas of a discipline structure. The relationships between authors are narrow and direct and feature multiple levels in AKCA. (2) All-author coupling provides a comprehensive picture; thus, a complete view of a discipline structure may require both first- and all-author coupling analyses. (3) Information science evolved continuously during the second decade of the World Wide Web. The KDA (knowledge domain analysis) camp became remarkably prominent, while the IR camp (information retrieval) experienced a further decline in hard IR research, and became significantly smaller; Patent analysis and Open Access emerged during this period. Mapping of Science and Bibliometric evaluation also experienced substantial growth. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:132 / 150
页数:19
相关论文
共 46 条
[1]   Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient [J].
Ahlgren, P ;
Jarneving, B ;
Rousseau, R .
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 2003, 54 (06) :550-560
[2]  
[Anonymous], 1996, UCINET IV: Network Analysis Software
[3]  
Reference Manual
[4]   Co-Citation Analysis, Bibliographic Coupling, and Direct Citation: Which Citation Approach Represents the Research Front Most Accurately? [J].
Boyack, Kevin W. ;
Klavans, Richard .
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 2010, 61 (12) :2389-2404
[5]   The Structure and Dynamics of Cocitation Clusters: A Multiple-Perspective Cocitation Analysis [J].
Chen, Chaomei ;
Ibekwe-SanJuan, Fidelia ;
Hou, Jianhua .
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 2010, 61 (07) :1386-1409
[6]   Research trends in gender differences in higher education and science: a co-word analysis [J].
Dehdarirad, Tahereh ;
Villarroya, Anna ;
Barrios, Maite .
SCIENTOMETRICS, 2014, 101 (01) :273-290
[7]  
He Q, 1999, LIBR TRENDS, V48, P133
[8]  
Hollstein B., 2011, SAGE HDB SOCIAL NETW
[9]  
Huang M. H., 2014, SCIENTOMETRICS, P1
[10]   A comparison of two bibliometric methods for mapping of the research front [J].
Jarneving, B .
SCIENTOMETRICS, 2005, 65 (02) :245-263