考察某领域研究的学术会议对本领域科研工作具有重要意义.文章以第一届``系统科学大会" (CSSC2017)的399篇投稿为数据基础,采用自然语言处理相关方法对数据预处理后构建关键词网络、合著网络、作者共享关键词网络以及机构共享关键词网络等单模网,基于社会网络分析的方法对网络结构以及节点中心性进行探析,通过网络分析工具Gephi可视化系统科学领域当前研究热点、研究人员、研究机构等之间的关系,进而定量地考察系统科学大会所反映的该领域的地域特性、学科特性以及合作状况,最后通过构建关键词/领域、作者/领域和机构/领域3个二模网络进一步分析研究焦点、作者、机构与领域之间的关系.

Tracing flagship conference papers may be quite helpful to research in relevant domain. Based on the 399 submissions of CSSC2017, this paper applies natural language processing methods to preprocess the data and then constructs single mode networks such as keyword network, co-authorship network, author-sharing-keyword network and organization-sharing-keyword network to obtain a rough knowledge vision including the main topics, the influential researchers and the relevant institutions of the systems science by using social network analysis and the network analysis tool Gephi. The study quantitatively exposes the geographical characteristics, disciplinary characteristics and cooperation status of the systems science area. At last, we establish the two-mode networks for further analysis of the relationship of research foci, researchers, institutions and submission fields.