Bio

Welcome!

I am Jacqueline Giacoman, a PhD candidate in Political Science at the University of California, Merced and a research fellow at the Political Violence Lab.

My research sits at the intersection of international relations, information flows and data construction in global media systems, and computational methods. I study how global news coverage shapes what we think we know about political violence and migration, and just as importantly, what we don’t see. Much of my work focuses on identifying systematic biases in international reporting, particularly the underrepresentation of certain types of events and regions. My goal is to design end-to-end, reproducible pipelines that combine computational methods with substantive questions in political science.

I employ a range of quantitative and computational methods to study large-scale patterns in political data. I have extensive experience working with APIs and building automated pipelines to collect, clean, and structure data from diverse sources, including text, geospatial, and visual data. My work relies primarily on R and Python for data processing, statistical analysis, and visualization, alongside Bash and Linux-based workflows for managing large datasets in high-performance computing (HPC) environments. 

In addition, I work with large language models (LLMs) and vision-language models (VLMs) through platforms such as Ollama and Hugging Face, applying them to tasks such as classification, bias detection, and multimodal analysis. I also develop custom approaches using dictionary-based methods and open-vocabulary detection to extract meaningful information from unstructured data. 

My dissertation examines how geopolitical relationships, editorial incentives, and technological constraints shape patterns of media attention, and develops methods to improve how these patterns are measured and interpreted. More broadly, I am interested in how the data we rely on in political science is produced, and how those processes influence what we know about politics and how it affects policymaking.