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The combination of social network extraction from texts, network analytics to identify key actors, and then simulation to assess alternative interventions in terms of their impact on the network is a powerful approach for supporting crisis de-escalation activities. In this paper, we describe how researchers used this approach as part of a scenario-driven modeling effort. We demonstrate the strength of going from data-to-model and the advantages of data-driven simulation. We conclude with a discussion of the limitations of this approach for the chosen policy domain and our anticipated future steps.