Target Policy-making Under the Frame of Dark Networks: Strengths, Weaknesses, and Opportunities
The Intelligence community utilizes Social Network Analysis (SNA) as an analytical tool-of-choice in many aspects of its investigation into criminal, terrorist, and foreign adversarial networks. The topical domain of Dark Networks attempts to frame the concepts and methodologies of SNA with classical decision science to formulate a collection of policies used by U.S. federal and state entities. However, scant evidence exists that the formulation of Dark Networks offers little more than classical SNA to begin with. In this session, we will discuss various ways by which we can enhance policymaking by strengthening the framework in ways classical SNA has yet to adopt, mainly through an information-theoretic approach. We will discuss current weaknesses and opportunities for developing the topic, especially in using agent-based simulations. The session will be relevant to scholars focused on political science, SNA, and computational social science in general.