Three new bibliometric indicators/approaches derived from keyword analysis

Mengyang Wang () and Lihe Chai
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Mengyang Wang: Tianjin University
Lihe Chai: Tianjin University

Scientometrics, 2018, vol. 116, issue 2, No 4, 750 pages

Abstract: Abstract Keyword analysis has been an important research theme in bibliometrics. The deduction of new valuable bibliometric indicators/approaches through keyword analysis is important for prompting the further development of this subject area. In this study, the following three bibliometric indicators/approaches were thus derived. Indicator K was derived using the ratio between the average unique keyword number and average keyword frequency of a discipline for quantitatively describing the discipline’s development stages highlighted by scientific-philosopher Kuhn. Next, the correlation matrix analysis was used after k-core filtration to quantitatively expose the detailed correlations between topics for a large network. Thirdly, indicators I (node betweenness divided by node degree) and C (clustering coefficient) were collectively introduced to predict potential growth keywords. Diverse topical evolutions were categorized into a strategic diagram according to the tendencies of I and C. With sustainable development as a case study, we verified that the three new bibliometric indicators/approaches work well and can realize many new concepts beyond the scope of available indicators or approaches. In summary, the present paper makes a renewed effort to promote the development of bibliometrics. We hope our work could catalyze the further studies from the communities in the scientometric fields.

Keywords: Keyword analysis; K indicator; k-Core; Correlation matrix; I–C indicator; Co-word network (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s11192-018-2768-9

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