PaCE
Patterns of Conflict Emergence
PaCE (Patterns of Conflict Emergence) is a five-year European Research Council (ERC) funded project (2022-26), based in the Department of Political Science at Trinity College Dublin. The project aims to uncover recurring patterns and temporal sequences in the run-up to war and conflict, and through the use of machine-learning methods, provide tools to forecast interstate and civil wars, with a range of data from financial markets, news articles, diplomatic documents and satellite imagery.
Background to the Research
There have been more than 200 wars since the start of the 20th century, leading to 35 million battle deaths and countless more civilian casualties. Large-scale political violence still kills hundreds every day across the world. International conflicts and civil wars also lead to forced migration, disastrous economic consequences, weakened political systems, and poverty.The recurrence of wars despite their tremendous economic, social, and institutional costs, may suggest that we are doomed to repeat the errors of the past. Does history indeed repeat itself? Are there particular temporal patterns in the build up to the onset of wars? Would better understanding of these patterns help us to avoid such conflicts?
Recent advances overcoming methodological and data barriers present an opportunity to identify these recurrences empirically and to examine whether these patterns can be classified to improve forecasts and inform theories of conflict. Just as DNA sequencing has been critical to medical diagnoses, PaCE aims to diagnose international politics by uncovering the relevant patterns around conflict. The project aims to uncover, cluster, and classify such patterns in meaningful ways to help us improve future forecasts.
Research Focus
Our Research Team is investigating a wide range of data, exploring financial, migration, protest and climate patterns. Certain indicators may follow a typical path — a motif — prior to conflict events (whether inter- or intra-state). Are the variables associated with conflict chaotic and therefore inherently unpredictable? Using novel methods in social sciences, we search for patterns in the observable actions that international leaders and actors take prior to conflict events, as well as in their perceptions. This will be done at multiple levels of resolution—the minute, the month, the year—and using original data on financial assets, news articles, and diplomatic cables.
Funding: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement no: 101002240).
