A select collection of personal research projects—including ongoing and past work—and areas I explore on my own time. This section excludes any work I do not directly lead or co-lead. All of these were undertaken at the doctoral level or higher.
Second Raven. (Newsletter).
Dr. Ryan Kennedy, Dr. William Minozzi, Dr. Laura Moses, The Ohio State University
We are a group of researchers affiliated with the Institute for Democratic Engagement and Accountability (IDEA) and the Machine-Assisted Human Decision-making (MAHD) Lab at The Ohio State University. We use artificial intelligence (AI) and unique analysis techniques to reveal the ways public opinion research and reporting warp our views of U.S. society and of each other.
AI Detector for Open-Ended Survey Data.
Priorietary model built for Survey 160 that analyzes open-ended survey responses and assigns probability scores indicating the likelihood that a given answer was AI-generated.
citehelpR package for R. (Github Repo).
This package checks and converts references in academic documents. It flags missing in-text citations or references in a document and can convert stand-alone reference lists between APA and Chicago styles.
dopplR package for R. (GitHub Repo).
Dr. Ryan Kennedy, The Ohio State University
This package generates and evaluates synthetic survey data. It can simulate responses based on real respondents profiles, create synthetic respondents and datasets that mirror the structure and distributions of real data, and generate multiple synthetic data variations. Additional features include weighting synthetic respondents to match target marginals, summarizing dataframe structures, comparing distributions with Komolgorov-Smirnov (KS) tests, and flagging synthetic data that may be too similar to the original.
2025-2026. Echoes of Conspiracy: Tracing Deep-State Rhetoric in Congressional E-Newsletters.
Dr. Joanne Miller, University of Delaware
We examine how members of Congress amplify or challenge deep-state conspiracy theories in their constituent communications and track how conspiracy-laden narratives spread across Congress. I trained an LLM to analyze a comprehensive database of congressional e-newsletters, creating a coding framework to identify conspiracy-related language and test its reliability against human annotations. I then use these classifications to track when and where conspiracy references appear, compare patterns across parties and individual legislators, and assess how these narratives move through the institution over time.
* Project funded by the Institute for Humane Studies (Grant No. IHS019471).
Doctoral Dissertation. Negative Public Opinion: How Normalized Out-Group Biases Shape Politics.
More information and relevant files and links can be found here: https://stephpedron.com/dissertation/.
Stephanie Pedron 