Publications
Published
Extractive versus Generative Language Models for Political Conflict Text Classification Political Analysis, 2025 Link | Slides | Code We develop specialized language models for political conflict analysis that outperform general-purpose LLMs like Gemma 2, Llama 3.1, and Qwen 2.5 in accuracy, precision, and recall while being hundreds of times faster.
ConflLlama: Domain-Specific Adaptation of Large Language Models for Conflict Event Classification Research & Politics, 2025 Link | Slides | Code We introduce ConflLlama, a specialized variant of Llama 3.1 fine-tuned for political conflict classification, demonstrating superior performance in event coding and conflict analysis tasks compared to traditional approaches.
Public Health Advocacy in Times of Pandemic: An Analysis of the Medicare-For-All Debate on Twitter During COVID-19 Behavioral Sciences, 2025 Link | Code We analyze how health advocacy groups adapted their Medicare-For-All messaging on Twitter during the COVID-19 pandemic, revealing distinct approaches to public engagement and narrative adaptation.
Under Review
Strategic Anticipation and Expert Review: The Determinants of Critical Advisory Opinions from the Dutch Council of State What determines whether an expert advisory body issues a critical opinion on a legislative proposal? Using a novel dataset of 2,129 advisory opinions (2004–2025), we find that ideological distance is the most robust predictor of opinion severity, while anticipatory compliance by vulnerable actors reverses expected patterns.
Framework Laws and Fading Oversight: How the Dutch Executive Expanded Its Lawmaking Authority Examining executive predominance in the Netherlands using a legislative dataset spanning 2000–2025. Roughly 75% of legislation now takes the form of secondary executive acts, while MPs retreat toward weaker oversight tools such as motions and parliamentary questions.
Democracy and Internet Control: Theory and Evidence from Transparency Reports Examining how democratic and authoritarian regimes differ in their approach to internet content moderation, using data from transparency reports.
Two Types of Censorship? An Assessment of the Informational Autocracy Thesis Testing how Guriev & Treisman’s Informational Autocracy theory applies to internet filtering practices in autocratic nations.
Build, Borrow, or Just Fine-Tune? A Political Scientist’s Guide to Choosing NLP Models Paper | Code A practical decision framework for political scientists choosing among domain-pretrained, fine-tuned, and commercial LLM approaches for text classification. Fine-tuning general-purpose encoders matches domain-pretrained alternatives and outperforms commercial APIs at a fraction of the cost.
Working Papers
Populism and Investment Treaties Investigating how nationalist rhetoric influences countries’ decisions to exit international investment agreements.
IGO Withdrawal Networks Extending Borzyskowski & Vabulas (2019) to examine network effects in international organization withdrawals.
Media Polarization in International News Coverage Using machine learning to analyze ideological patterns in international news coverage across 200,000+ articles.
Event Horizon: Revolutionizing Data Annotation with Reinforcement Learning Model A novel reinforcement learning framework built on DeepSeek’s GRPO, merging political science with advanced AI to create structured, transparent annotations for complex events.
Dissertation
Digital Sovereignty: The Political Economy of Internet Governance University of Texas at Dallas, 2025 Slides