Welcome! I am a Ph.D. candidate at New York University’s Politics Department. My substantive specialization is on the comparative politics of authoritarian regimes with a focus on Chinese politics. My methodological focus lies in applying text as data and machine learning tools towards understanding the behavior of regimes, media, and their citizenry.
In my first dissertation paper, I test whether Chinese state media engages in a strategy of “negative legitimation” by portraying the politics of liberal democracies as being chaotic. Using a novel method of measuring propaganda, I find robust evidence that is consistent with a negative legitimation strategy. My second dissertation paper expands on this result, finding that China’s state media targets executive elections in liberal democracies for unfavorable coverage.
One challenge I faced in my other dissertation projects was identifying Chinese-language semantically-related dictionaries. I address this need in my third dissertation project, where I present conclust, an algorithm based on word embeddings, that enables researchers to derive semantically related keywords using only 3-5 seed words. In addition to this paper, I have contributed to making neural network machine learning models accessible to a broader audience by writing functions for the quanteda.classifiers package.
Download my resumé.
Ph.D. in Politics (ABD), 2022 (est)
New York University
Master of Pacific International Affairs, 2014
School of Global Policy and Strategy at University of California: San Diego
Bachelor of the Arts in Political Science, 2009
University of Minnesota: Morris
“Deligitimizing Election Coverage: Identifying a Negative Legitimation Strategy in China’s Coverage of Foreign Elections”
“Embedded Lexica: Extracting Topical Dictionaries from Unlabeled Corpora using Word Embeddings”
“Vaccine Nationalism: Propaganda and China’s Media Coverage of Vaccines”
with Victor Shih
“Informational Statecraft and Diaspora Mobilization”
with Audrye Wong
“Predicting Left-Right Positions from Hand-Coded Content Analysis using Machine Learning”
with Kenneth Benoit, Michael Laver, and Stefan Muller
“Extracting Measurements of De Jure Power from Constitutional Text”
“Networks of Power: Extracting Measurements of De Jure Power from Constitutional Text”
“Over-fishing, Conflict, and the South China Sea”
with Junjie Zhang