Mark Whitlock on "Big Data and Conflict Prevention"

The global explosion of Big Data promises to be one of the most important social developments of the early 21st century. Rapidly improving sensing techniques combined with advancements in machine learning allow innovators to leverage massive, unstructured data in fields as diverse as earth science, public health, economics, business, political campaigning, education, and diplomacy.

However, big data’s implications for the interdisciplinary field of conflict studies are less understood. The growth of this phenomenon, and the subsequent development of powerful algorithms for data mining, far outpace extant literature measuring its utility in the early warning, analysis, prevention, and management of intergroup conflict and larger political violence.

This research is an attempt to synthesize the interdisciplinary literature from social and computer science, survey current efforts at implementation of big data analytics in international conflict, and explore strategies for improving impact including sensing, visualization, analysis and response.

The increasing complexity and interconnectedness of violent conflict and subsequent management systems, coupled with the technological advancements driving big data analytics, incentivize increased collaboration across the academy - between social scientists of historically siloed disciplines, and with computer scientists and statisticians.

To better understand the promise of big data analytics in conflict early warning and prevention, it is necessary to explore multiple bodies of literature including theories of conflict and prevention, the psychology and politics of decision-making in the social sciences, and advancements in machine learning in computer science.