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Mapping topics and topic bursts in PNAS

机译：在PNAS中映射主题和主题突发

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摘要

Scientific research is highly dynamic. New areas of science continually evolve; others gain or lose importance, merge, or split. Due to the steady increase in the number of scientific publications, it is hard to keep an overview of the structure and dynamic development of one's own field of science, much less all scientific domains. However, knowledge of "hot" topics, emergent research frontiers, or change of focus in certain areas is a critical component of resource allocation decisions in research laboratories, governmental institutions, and corporations. This paper demonstrates the utilization of Kleinberg's burst detection algorithm, co-word occurrence analysis, and graph layout techniques to generate maps that support the identification of major research topics and trends. The approach was applied to analyze and map the complete set of papers published in PNAS in the years 1982-2001. Six domain experts examined and commented on the resulting maps in an attempt to reconstruct the evolution of major research areas covered by PNAS.
机译：科学研究是高度动态的。科学的新领域不断发展。其他人获得或失去重要性，合并或分裂。由于科学出版物数量的稳步增长，很难对自己的科学领域的结构和动态发展进行概览，更不用说所有科学领域了。但是，对“热门”主题，新兴研究前沿或某些领域的关注焦点的了解是研究实验室，政府机构和公司中资源分配决策的关键组成部分。本文演示了利用Kleinberg的突发检测算法，共词出现分析和图形布局技术来生成地图，以支持对主要研究主题和趋势的识别。该方法用于分析和绘制1982-2001年间在PNAS上发表的整套论文。六位领域专家检查了所生成的地图并对其进行了评论，以试图重建PNAS涵盖的主要研究领域的演变。

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