Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis
Siluo Yang,
Ruizhen Han,
Dietmar Wolfram and
Yuehua Zhao
Journal of Informetrics, 2016, vol. 10, issue 1, 132-150
Abstract:
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.
Keywords: Author keyword coupling analysis; Information science; Author bibliographic coupling analysis; Bibliometric mapping (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (22)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:10:y:2016:i:1:p:132-150
DOI: 10.1016/j.joi.2015.12.003
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