The evolution of scientific fields has been attracting much attention in recent years. One of the key issues in evolution of scientific field is to quantify the dissimilarity between two collections of scientific publications in literature. Many existing works study the evolution based on one or two dissimilarity measures, despite the fact that there are many different dissimilarity measures. Finding the appropriate dissimilarity measures among such a collection of choices is of fundamental importance to the study of scientific evolution. In this article, we develop a new measure of the evolution combining twelve keyword-based temporal dissimilarities of the scientific fields using the method of principal component analysis. To demonstrate the usage of this new measure, we chose four scientific fields: environmental studies, information science & library science, mechanical informatics, and religion. A database consisting of 274453 bibliographic records in these four chosen fields from 1991 to 2019 are built. The results show that all these four scientific fields share an overall decreasing trend in evolution from 1991 to 2019 and different fields exhibits different evolution patterns during different time periods.

中文翻译：

---

结合相异性测度研究科学领域的演化

近年来，科学领域的发展吸引了很多关注。科学领域发展的关键问题之一是量化文学中科学出版物的两个集合之间的差异。尽管存在许多不同的差异度量，但许多现有的作品都基于一种或两种不同的度量来研究演化。在这样的选择集合中找到适当的相异性度量对科学进化的研究具有根本的重要性。在本文中，我们使用主成分分析方法，结合了科学领域中基于关键字的十二种时空差异，开发了一种新的进化测度。为了演示这项新措施的用法，我们选择了四个科学领域：环境研究，信息科学与图书馆科学，机械信息学和宗教。建立了一个数据库，该数据库包含1991年至2019年这四个选定领域中的274453个书目记录。结果表明，从1991年到2019年，这四个科学领域的演化总体上呈下降趋势，不同领域在不同时期表现出不同的演化模式。