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Combining dissimilarity measures for quantifying changes in research fields
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DOI：10.1007/s11192-022-04415-5.png)
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Abstract
En 中文
The changes in research fields has been attracting much attention in recent years. One of the key issues here is to quantify the dissimilarity between two collections of scientific publications in literature. Many existing works on this topic based their study on one or two dissimilarity measures, despite the fact that there are numerous such dissimilarity measures. It is of fundamental importance to find appropriate dissimilarity measures among such a sizeable collection of choices. In this article, we develop a new measure of the evolution combining 12 keyword-based temporal dissimilarities of the research fields using the method of principal component analysis. To demonstrate the usage of this new measure, we chose four research fields: environmental science, information science and library science, medical informatics, and religion. A database consisting of 274,453 bibliographic records in these four chosen fields from 1991 to 2019 are built. The results show that all these four research fields share an overall decreasing trend in evolution from 1991 to 2019 and different fields exhibits different evolution patterns during different time periods.
Keywords:
Dissimilarity measures
Measure of evolution
Principal component analysis
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