Search
Browse By Day
Browse By Time
Browse By Person
Browse By Mini-Conference
Browse By Division
Browse By Session or Event Type
Browse Sessions by Fields of Interest
Browse Papers by Fields of Interest
Search Tips
Virtual Exhibit Hall
Change Preferences / Time Zone
Sign In
X (Twitter)
Researchers and policymakers have increasingly argued that international order influences a host of political processes in the international system. Yet we still do not understand where international orders come from and how they influence conflict, and the coarseness of existing measures of international order makes these questions difficult to answer with much certainty. In the presented piece, we derive a new and more nuanced measure of international order, derived from states' characteristics and dyadic interactions and compiled using network analysis and machine learning techniques. Our analytic approach yields two significant findings. First, we explore the relationship between shared international order and conflict between states. Second, we aggregate states to the international order level and examine how the differences between the characteristics of international orders lead to different patterns of conflict.