Hannah Frank: 4th Year PhD Student

Can you give us a brief overview of your research and what inspired you to choose this topic?

My PhD research focuses on transitions in armed conflict. Why does collective action occur? And how does collective action transition to civil war? In answering these questions, tools from machine learning are promising since they can uncover empirical associations in the context of complex phenomena, such as armed conflict. War is the most puzzling social phenomenon because it leads to tremendous human suffering.

What has been the most surprising or interesting finding in your research so far?

For highly complex social phenomena, we need a “many-model thinking” approach (term coined by Scott E. Page). When studying armed conflict, there is no single explanation that can account for all civil wars. Rather, armed conflict is caused by a multitude of factors, often showing non-linear and conditional associations.

How do you think your research could impact the field of political science or society as a whole?

Leveraging machine learning to validate civil conflict theory can shed light on some remaining questions. The goal is to produce knowledge that is relevant for practitioners working on conflict prevention. A better understanding of the causes of and transitions in armed conflict might assist in mitigating more serious escalations of violence.

What advice would you give to other students who are considering pursuing a PhD in political science?

The most important aspect of pursuing a PhD is the research topic. It is key to carefully choose a social phenomenon that you strongly believe needs to be researched.

Learn more about the Political Science PhD Programme