Agustin Prinetti

PhD Candidate in Political Science, Rice University. Visiting fellow, Centre for Political Research (CEVIPOF), Sciences Po. Editorial assistant, International Organization.

I am a PhD candidate in Political Science at Rice University. This semester, I will be a visiting fellow at the Centre for Political Research at Sciences Po. I also serve as the editorial assistant for International Organization.

I work on the intersection of comparative politics, communication, and technology. My research explores the adoption of new digital tools, with a focus on AI chatbots, and their influence on the ways citizens learn about and engage with politics.

Originally from Argentina, I began my journey in Political Science at Universidad Torcuato Di Tella. Before starting my PhD, I worked as a Research Analyst for the Government of the City of Buenos Aires.

Outside of academia, I enjoy learning languages: I am fluent in English, Spanish, and Italian, and I currently study French. I also enjoy swimming and rewatching The Simpsons.

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Research Agenda: The Dark Side of Online Political Behavior

I study how citizens in different countries interact with political content on social media that is deceptive, hostile, or extremist. My research examines how users engage with that content and how it influences their political behavior. Methodologically, I combine the observational study of social media data with immersive online experiments that closely recreate real-world digital environments.

  • Misinformation & Factual Verification
  • Political Manipulation of AI Chatbots
  • Moderation of Extremist Content
  • Campaign Negativity & Attack Advertising

Dissertation

For years, research has shown that factual corrections can, in most settings, limit the harmful effects of political misinformation. Despite this, major social media platforms are currently retreating from partnerships with professional fact-checkers and adopting new verification systems that bypass journalists and experts.

My dissertation examines the newest of these developments: the growing use of AI chatbots to verify political information.

I study how political contexts shape the ways people adopt these tools and assess whether they can potentially substitute human fact-checkers.

Working Papers

Do Androids Dream of Corrective Tweets? The Reliance of AI Factual Verification on Professional Fact-Checking

Prinetti, Agustin. Preprint (SSRN)

Can AI chatbots replace humans in the fight against online political misinformation? As partnerships between professional fact-checkers and social media companies erode, platforms have started promoting AI-based replacements. Motivated by political communication research documenting a trade-off between speed and accuracy in fact-checking, I argue that AI tools may exacerbate this pattern. I focus on Grok, the AI chatbot integrated into X (formerly Twitter) and promoted as a factual verification tool. Through an observational study of Grok's verifications over time and a controlled design that manipulates its access to external sources, I show that Grok's accuracy increases as professional fact-checking articles become available, and that its access to them is a substantial driver of its performance. These findings suggest that AI should be understood as a complement rather than a substitute for fact-checkers, as its accuracy depends, to a relevant extent, on the same human activity it seeks to replace.

Designing for Power: Covariates, Indices, and Efficiency in Survey Experiments

Peterson, Erik, Matthew Tyler, and Agustin Prinetti. Preprint (SSRN)

Survey experiments are widely used across the social sciences, yet many are underpowered. We examine two well-known, but unevenly applied, strategies for improving statistical efficiency: covariate adjustment and multi-item index outcomes. We formally evaluate when these practices increase power and revisit over four hundred recent social science survey experiments to empirically assess their prevalence and effectiveness. We show these techniques reduce distinct sources of variance and function as complements, not substitutes, for increasing power. However, the majority of survey experiments omit these practices or employ them ineffectively by adjusting for generic demographic covariates that yield minimal precision gains. Only a small minority of studies use specialized covariates or index outcomes. Fewer than five percent combine both practices. Drawing on simulations based on recent studies, we argue designs combining specialized covariates with a short index outcome offer a practical and robust way to increase the statistical power of survey experiments.

Bystanders on Social Media: Audience Moderation and the Spread of Political Extremism

Joyce, Conner B., Maranda Joyce, and Agustin Prinetti. Manuscript

What explains participation in crowd moderation on social media platforms? Social media platforms rely on crowd moderation (the reporting of extremist content by users) to identify and remove harmful content. We argue that participation in crowd moderation can be explained by the Volunteer's Dilemma Game, where users' decision to report is a function of the benefits, costs, and number of other observers. We expect that when users encounter a greater number of extremist posts or they believe that others will report extremist content, their inclination to participate in crowd moderation is depressed. We test these expectations by employing a novel experimental approach in which subjects interact with social media feeds that simulate online environments. Our study would help explain crowd moderation's shortcomings and the widespread circulation of extremist content on social media platforms.

Campaign Negativity and Political Participation in the Social Media Era

Prinetti, Agustin, Asahi Obata, and Randy Stevenson. In progress.

Do negative political campaigns lead to lower political participation? We revisit this question in the current era of multiple social and media platforms. While several studies have explored whether negative campaigns on traditional media lead to demobilization, we argue that this relationship is conditional on the media voters see negative campaigning on. We test this through the first immersive artefactual field experiment in the study of social media platforms.

Research Funding

Institutions that supported me with grants and fellowships to conduct and present my research during my PhD: Rice University's School of Social Sciences, Fulbright, Chateaubriand Fellowship, APSA, SPSA, and CIISR.

Teaching

I have worked as a TA for graduate-level courses on statistics and quantitative methods, and for undergraduate-level substantive classes, both in English and Spanish. I have experience leading discussion sections and evaluating students' performance through assignments and exams. In 2024, I completed Rice's Graduate Certificate in Teaching and Learning.

  • Introduction to Maximum Likelihood Estimation I and II (PhD level, Rice University, Fall 2025 and Spring 2026, Prof. Randy Stevenson; average student rating 5.0/5)
  • Quantitative Applications in Global Affairs (Master's level, Baker Institute / Rice University, Fall 2024 and Fall 2025, Prof. Daniel Potter; average student rating 4.9/5)
  • Introduction to American Politics (Undergraduate level, Rice University, Fall 2023, Prof. Jaclyn Kaslovsky; average student rating 4.4/5)
  • Comparative Political Systems (Undergraduate level, Universidad Torcuato Di Tella, 2021, Prof. Ana Maria Mustapic; average student rating 4.3/5)