LAUSR

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.