Abstract: Modeling the repression-dissent nexus has long been an empirical challenge. For one thing, such paired actions are endogenously determined as parts of an ongoing strategic interaction between dissidents and the state. For another, both repression and dissent comprise a wide variety of tactics only imperfectly captured in standard violent-nonviolent empirical dichotomies. This latter point becomes important if each side’s strategic response varies according to the other’s tactics. I propose a novel approach built on network analysis to study the repression-dissent dynamic. First, I develop a network of interdependent tactics and strategies focused on actions, rather than actors. I am thus able to map out tactic-to-tactic interactions in resistance movements and explore clusters of strategy substitutions between the state and the dissidents. Second, I show that considering disaggregated actions and simultaneous repression and dissent in a network framework significantly improves our ability to forecast different types of state repression at the event level. Lastly, I show that applying this network approach also helps explain the important conflict escalation and de-escalation process in anti-government campaigns. Generating predictions and explaining conflict escalation are both important for our understanding of strategic interdependence and formulating policy in the context of dissent movements.