Dim networks: the utility of social network analysis for illuminating partner security force networks

As the security landscape changes, the importance of strong and influential partnerships for security cooperation (SC) increases. The process of selecting the best possible partners should not be neglected; tools to accomplish this task may already exist. Recently, the use of social network analysis (SNA) has allowed the military to map dark networks of terrorist organizations and selectively target key elements. SNA data collection and analysis efforts remain focused on these terrorist networks, whereas friendly or light networks have been relatively neglected. This thesis highlights the importance of analyzing light networks for SC and introduces the concept of dim networks. These are networks that consist of friendly actors whose connections to external organizations may not be public. This thesis has potential to improve partner security force engagement selection through the use of SNA principles, methods, and software, yielding several dividends. First, it provides a commander with a detailed understanding of the foreign units involved in SC, which allows for development of a more focused engagement strategy. Second, it allows SC planners to invest time and resources on the partner security forces that most effectively advance the commander’s engagement priorities. Third, it reinforces the collection of network-related data on organizations the U.S. military cooperates with and the importance of analyzing that empirical data to improve SC.http://archive.org/details/dimnetworksutili1094547943Major, United States ArmyApproved for public release; distribution is unlimited