More than half of the countries in the international system have experienced a civil war in recent decades and a growing number of countries face violent internal conflicts. The majority of civil conflicts since 1946 have had at least three active armed groups and some have had up to ten groups, yet most analyses only examine interactions between the government and an assumed homogeneous opposition group. Research has fallen short in measuring and modeling techniques that adequately capture network and relational characteristics essential to the data-generating process needed for understanding civil conflict. This project unmasks the interdependent dynamics of civil conflict by conceptualizing actors and battles as a set of nodes and ties that constitute a network. The project will generate a user-friendly statistical package and website, called conflictNet, that will allow researchers to more easily conceptualize and study civil war.
A growing body of literature demonstrates that controlling for interdependence in relational data yields less biased parameter estimates and allows us to better understand how conflict will evolve. ConflictNet will be a valuable contribution to the field and enable scholars interested in the analysis of current political events and civil conflict in two keys ways. First, from a modeling perspective, the creation of a tool that allows for the easy generation of network data on subnational-level conflict will improve the ability to conduct inference on the drivers of civil conflict, and operationalizing conflict between armed actors using a network perspective will allow for greater accuracy in forecasting future occurrences of conflict. Second, this project not only addresses critical gaps in the literature but also paves the way for new directions in intrastate conflict research: the prediction of battle-level incidents at fine-grained unit of analyses; new hypotheses on how violent events are conditional on the ebb and flow of group level characteristics, motivations, and socio-political connections; and a deeper understanding of how interdependence across armed actors escalates violence against civilians and poses new challenges for government actors.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
