大科学时代，从共生视角对院士科学合作的结构特征和演化趋势进行探测研究，有助于从科学合作内在本质属性揭示科学合作网络的本质特征和发展路径。本项目基于主题模型方法，结合社会网络分析技术，利用世界权威引文数据库Web of Science海量文献数据，从院士科学合作网络的共生强度、跨界性、集群性、合作主体的亲缘性及兴趣共享度等多个视角，建构“院士科学合作共生网络”的多维测度指标体系，综合应用科学计量学的各种量化分析方法，分别从宏观和微观角度定量揭示院士科学合作网络的结构特征，追踪和系统描绘合作网络的演化趋势，并结合信息可视化技术形象展现科学合作网络的结构模式和演化趋势。研究成果将丰富和发展科学学理论，拓展生态学方法及其在科学计量学中的应用范围，为科学合作研究提供新的视角。基于科学合作网络演化趋势探测新兴领域和主题，将有助于科技人员更准确、深入地把握新兴领域的前沿进展和发展动态。

In the age of Big Science，from the perspective of symbiosis to study the structure and evolution of the scientific collaboration network of academicians, is of great significant for us to grasp the intrinsic characteristics and development path of scientific collaboration network from the scientific collaboration’s intrinsic nature attribute. Based on Topic Models analysis and Social Network analysis, and adopting mass literature data from the world-authority literature database “Web of Science”, take the academicians of Chinese Academy of Sciences (CAS) and United States National Academy of Sciences (NAS) as examples, from the multiple perspectives of scientific collaboration network of academicians: symbiosis intensity，transboundary，clustering，affinity and interest sharing degree of collaborative agent，we will construct multidimensional measure index system of scientific collaboration symbiotic network of academicians. Furthermore, applying various quantitative analysis methods of scientometrics, from the macro and micro perspectives respectively，we will reveal the structure of the scientific collaboration network of academicians, also track and describe the evolution trend of the network. Using visualization technology，we display the structure and evolution trend of scientific cooperation network vividly. The research result of this project will enrich and develop the theory and method of Science of Science, moreover, will expand method and application of ecology and its application in scientometrics, which will provide new research perspective for scientific collaboration research. Exploring the emerging field and subject in the evolution trend of the network will help researchers grasp frontier progress and dynamic development of emerging field accurately and deeply.