科学发展史的重建
The Reconstruction of Science Phylogeny
摘要：
在应对科学生产的不断加速和科学性质的日益变化时，我们面临着真正的挑战。在这篇文章中，我们扩展了共词分析的经典框架，科学景观演变的研究。利用以前介绍的科学映射方法与重叠聚类，我们提出的方法来重建系统发育网络从连续的科学地图，并深入了解科学领域的各种动态。引入伪包含和经验质量两个指标对科学领域进行定性，并用于重构验证。系统发育动力学似乎与这两个指数有很强的相关性，而与先前引入的第三个指数（密度指数）的相关性较弱。这些结果表明，科学领域的“生命周期”存在着规律性的模式。科学发展史的重建应该会提高我们对科学进化的全球理解，并为我们与科学成果的日常互动开发创新工具铺平道路。从长远来看，这些方法应该引导定量认识论，以证实或证伪基于科学文献数据库的大规模进化重建的科学进化理论模型。
英文摘要：
We are facing a real challenge when coping with the continuous acceleration of scientific production and the increasingly changing nature of science. In this article, we extend the classical framework of co-word analysis to the study of scientific landscape evolution. Capitalizing on formerly introduced science mapping methods with overlapping clustering, we propose methods to reconstruct phylogenetic networks from successive science maps, and give insight into the various dynamics of scientific domains. Two indexes - the pseudo-inclusion and the empirical quality - are introduced to qualify scientific fields and are used for reconstruction validation purpose. Phylogenetic dynamics appear to be strongly correlated to these two indexes, and to a weaker extent, to a third one previously introduced (density index). These results suggest that there exist regular patterns in the "life cycle" of scientific fields. The reconstruction of science phylogeny should improve our global understanding of science evolution and pave the way toward the development of innovative tools for our daily interactions with its productions. Over the long run, these methods should lead quantitative epistemology up to the point to corroborate or falsify theoretical models of science evolution based on large-scale phylogeny reconstruction from databases of scientific literature.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
