Collaborative Research: Using Big Data to Analyze Maritime Conflict

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Maritime conflict has been on the rise globally, with hotspots across the world's regions. Despite growing coverage in the news media, among think tanks, and great attention from policy makers and politicians, there is limited systematic data on conflict incidents in maritime regions. This project will fill two important gaps. First, it will generate a multi-faceted dataset on maritime conflict that will be shared publicly for use by scholars and journalists. Second, although theorists have offered many competing accounts for what to expect in the realm of maritime conflict, there have yet to be any compelling empirical investigations of what has taken place in the past decade. This project will develop data collection techniques that will be applicable to a range of maritime conflict-affected regions, which also have substantial national security implications.Social scientists have increasingly turned to data-driven approaches to answer important questions regarding international security. Within the world of conflict research, comprehensive datasets have played a critical role in advancing scientific knowledge (e.g. AidData, COW, ACLED). Thus far, however, there has been limited systematic empirical analysis of maritime conflict; a major hurdle is a lack of data. In this project, the PIs acquire and consolidate comprehensive data on maritime incidents and make substantial progress toward empirically testing and resolving competing theories for how maritime conflict may play out over the next decade. The project refines prevailing theories of power transition, taking into account the slow but steady change in maritime capabilities of superpowers as well as the growing economic and political interdependence among nation-states since the end of the Cold War, to generate new testable hypotheses. The analysis utilizes the overlapping EEZ zones and territorial waters, variation in off-shore natural resource distribution, and changes in domestic politics to test the proposed hypotheses. The data will be made publicly available and legible to other social scientists so that experts can replicate it for their own research purposes.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.