Welcome! I’m an Assistant Professor in the Department of Political Science at the University of California, San Diego. My research interests lie in the intersection of political methodology and the politics of information, with a specific focus on methods of automated content analysis and the politics of censorship in China.

I received a PhD from Harvard in Government (2014), MS from Stanford in Statistics (2009) and BA from Stanford in International Relations and Economics (2009). Much of my research uses blogs, online experiments, and large collections of newspaper articles to understand the influence of censorship and propaganda on the spread of information in China.

Currently, I’m working on a variety of additional projects that span censorship, propaganda, topic models, and other methods of text analysis. Some of this work has appeared or is forthcoming in the American Journal of Political Science, American Political Science Review, Science, and Political Analysis.



Censored: Distraction and Diversion Inside China's Great Firewall describes how incomplete and porous censorship in China have an impact on information consumption in China, even when censorship is easy to circumvent. Using new methods to measure the influence of censorship and propaganda, I present a theory that explains how censorship impacts citizens' access to information and in turn why authoritarian regimes decide to use different types of censorship in different circumstances to control the spread of information. It is forthcoming with Princeton University Press.

Working Papers

William Hobbs and Margaret E. Roberts. 2016. “How Sudden Censorship Can Increase Access to Information”.

Naoki Egami, Christian Fong, Justin Grimmer, Margaret Roberts and Brandon Stewart. 2017. "How to Make Causal Inferences with Text."

Ben Liebman, Margaret Roberts, Rachel Stern and Alice Wang. 2017. "Mass Digitization of Chinese Court Cases: How to Use Text as Data in the Field of Chinese Law."

Roberts, Margaret E, Brandon M. Stewart and Richard Nielsen. “Matching Methods for High-Dimensional Data with Applications to Text.”

Horowitz M, Stewart B, Tingley D, Bishop M, Resnick L, Roberts M, Chang W, Mellers B, Tetlock P. “What Makes Foreign Policy Teams Tick: Explaining Variation in Group Performance At Geopolitical Forecasting.”

Published Papers


  • Gary King, Jennifer Pan, and Margaret E. Roberts. 2017. “How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument”. American Political Science Review. Copy at http://j.mp/1Txxiz1
  • King, Gary, Patrick Lam, and Margaret E. Roberts.  “Computer-Assisted Keyword and Document Set Discovery from Unstructured Text.” American Journal of Political Science. Copy here.


  • Roberts Margaret E, Stewart Brandon M, Airoldi Edo M.  “A model of text for experimentation in the social sciences.”  2016. Journal of the American Statistical Association.  Copy here.
  • Roberts, Margaret E, Stewart, Brandon, & Tingley, Dustin.  “Navigating the Local Modes of Big Data: The Case of Topic Models.” 2016. In Computational Social Science, New York: Cambridge University Press.  Copy here.


  • Chuang J, Roberts M, Stewart B, Weiss R, Tingley D, Grimmer J, Heer J. “TopicCheck: Interactive Alignment for Assessing Topic Model Stability“. North American Chapter of the Association for Computational Linguistics Human Language Technologies (NAACL HLT). 2015.
  • Monroe, Burt, Jennifer Pan, Margaret E. Roberts,  Maya Sen, and Betsy Sinclair.  2015.  “No! Formal Theory, Causal Inference, and Big Data Are Not Contradictory Trends in Political Science.”   PS: Political Science and Politics. 48, no 1 pg 71-41.
  • Reich, Justin, Tingley, Dustin, Leder-Luis, Jetson, Roberts, Margaret E., & Stewart, Brandon M.  “Computer Assisted Reading and Discovery for Student Generated Text.”  2015. Journal of Learning Analytics. Copy here.


  • Lucas, Christopher, Richard Nielsen, Margaret E. Roberts, Brandon M. Stewart, Alex Storer, and Dustin Tingley.  2014.  “Computer assisted text analysis for comparative politics.” Political Analysis Copy here.
  • Chuang J, Wilkerson JD, Weiss R, Tingley D, Stewart BM, Roberts ME, Poursabzi-Sangdeh F, Grimmer J, Findlater L, Boyd-Graber J, et al. Computer-Assisted Content Analysis: Topic Models for Exploring Multiple Subjective Interpretations. Advances in Neural Information Processing Systems Workshop on Human-Propelled Machine Learning. 2014.
  • King, Gary and Margaret E. Roberts. “How Robust Standard Errors Expose Methodological Problems They Do Not Fix.” Political Analysis 2014. copy here.
  • Roberts, Margaret E, Brandon Stewart, Dustin Tingley, Chris Lucas, Jetson Leder-Luis, Bethany Albertson, Shana Gadarian, and David Rand.   “Topic models for open-ended survey responses with applications to experiments.” forthcoming, American Journal of Political Science. (2014).  Copy here.
  • King, Gary, Jennifer Pan, and Margaret E. Roberts.  “Reverse Engineering Chinese Censorship: Randomized Experimentation and Participant Observation”  Science (2014). Copy here.  [press about the paper on NPR and in the WSJ


  • King, Gary, Jennifer Pan, and Margaret E. Roberts. “How Censorship in China Allows Government Criticism but Silences Collective Expression.” American Political Science Review (2013). copy at http://j.mp/LdVXqN [press about the paper in the WSJ and in the Economist
  • Roberts Margaret E, Stewart Brandon M, Tingley Dustin, Airoldi Edo M. “The Structural Topic Model and Applied Social Science.” Advances in Neural Information Processing Systems Workshop on Topic Models: Computation, Application, and Evaluation. 2013. Copy here Peer-Reviewed Conference Workshop. Selected for Oral Presentation.

Related Writings


The Structural Topic Model: R package stm for estimating the Structural Topic Model.

The Structural Topic Model Browser: R package stmBrowser for visualizing the Structural Topic Model.


Current Teaching

Political Science 170A

Winter 2015/2016

Introductory Statistics for Political Science and Public Policy.

Political Science 271

Winter 2015/2016

Advanced Statistical Applications.

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