Investigating Social Network Analysis Methods for Identifying Emergent Behaviors in Agent-Based Models
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Understanding social networks, their nature in influencing events and ways to impact them is critical to supporting key military activities such as counter-insurgency and counter-improvised explosive devices (C-IED). Preliminary work has been performed to explore methods of extracting, analyzing, and visualizing social networks that are emergent from many agent-based models. A simplified interaction scenario has been created to generate data to serve as the starting point for exploring the proposed techniques and tools. Test tools and prototype methods for data-farming the scenario, extracting network data, analyzing end-of-run network statistics, and visualizing network behaviors are identified and explored. Supporting tools include the agent-based model Pythagoras, the Social Network Image Animator (SoNIA), R Project for Statistical Computing (S routines for social network analysis), and PlotGL. This paper summarizes preliminary work with the data farming and analysis techniques being explored.
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