Situational awareness and intelligence mining in national security research based on complex network models

Scientific research collaboration in the field of national security is becoming increasingly complex. The expansion of national security disciplines and the diversification of collaborative models have had a profound impact on innovation and development in this domain. However, existing studies lack in-depth analysis of cross-institutional and cross-disciplinary collaboration, and they have not sufficiently revealed the critical role of independent research capacity in driving academic innovation. Based on open-source data from 1985 to 2022, this paper covers 4820 authors and 4799 national security-themed papers, employing complex network modeling to construct an author-centric scientific research collaboration network. A systematic analysis of the characteristics of the national security collaboration network is conducted at the macro, meso and micro levels. The results show that at the macro level, research collaboration is primarily concentrated within single institutions, while collaborations between two or more parties have increased year by year. Despite the expanding scale of the network, collaboration density has shown a downward trend. At the meso level, core research institutions have constructed tight community structures through cross-disciplinary and cross-regional collaboration, significantly promoting academic innovation. At the micro level, researchers with strong independent research capabilities, though having lower connectivity within the collaboration network, have made significant contributions to academic innovation through their independent work. This paper provides important insights for further strengthening cross-institutional collaboration and the role of independent research capacity in the national security field, laying a solid foundation for optimizing future scientific research collaboration models.