Patrick J. Chester

Patrick J. Chester

Postdoctoral researcher

The China Data Lab at University of California, San Diego

Biography

Welcome! I am a postdoctoral researcher at the China Data Lab at UC, San Diego. I received my PhD in political science from New York University’s Politics Department. I specialize in applying computational methods — including machine learning, large language models, and web scraping — to better understand the comparative politics of authoritarian regimes. My dissertation demonstrates a new method to measure propaganda using word embeddings and applies it towards determining whether Chinese media strategically portrays democracy as chaotic and corrupt. In my broader research agenda, I examine how China and other autocracies utilize propaganda and censorship to shape the opinions of both domestic and foreign audiences. To that end, I apply text as data and machine learning tools towards the measurement of political science concepts, such as propaganda, in text data. A list of my publications, working papers, and software can be found below.

Download my resumé.

Interests
  • Chinese politics
  • Computational social science
  • Comparative politics
  • Propaganda and framing
  • Text as data
  • Word embeddings
  • Web scraping
Education
  • Ph.D. in Politics, 2022

    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

Teaching Experience

 
 
 
 
 
Teaching Assistant for Introduction to Data Science Course
Feb 2021 – Present New York
Head TA for course introducing undergraduates to supervised machine learning using Python.
 
 
 
 
 
Teaching Assistant for American Politics Course
Sep 2020 – Dec 2020 New York

Responsibilities include:

  • Instructing students
  • Generating assignment and exam reports using Rmarkdown
 
 
 
 
 
Teaching Assistant for Comparative Politics Course
Sep 2019 – Dec 2019 New York
Taught students core concepts and theories associated with the the Comparative Politics subfield.
 
 
 
 
 
Teaching Assistant for International Politics Course
Feb 2018 – May 2018 New York
Instructed undergraduates in the state of academic research in the field of International Politics.
 
 
 
 
 
Teaching Assistant for Research Methods Course
Sep 2016 – Dec 2016 New York
  • Worked as head TA to prepare course materials and collaborate with other Teaching Assistants.
  • Taught undergraduate students basics of regression analysis, causal identification, and Stata.
 
 
 
 
 
Teaching Assistant for Text as Data course
Feb 2016 – May 2016 New York
Instructed graduate students how to perform supervised and unsupervised machine learning using R.

Skills

R
Python
Mandarin Chinese

Professional proficiency

Contact