Welcome! I’m a Professor in the Department of Political Science and the Halıcıoğlu Data Science Institute at the University of California, San Diego.  I co-direct the China Data Lab at the 21st Century China Center.   I am also an affiliate at the UC Institute on Global Conflict and Cooperation. 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 and propaganda 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 social media, online experiments, and large collections of texts to understand the influence of censorship and propaganda on access to information and beliefs about politics.

My first book, Censored: Distraction and Diversion Inside China’s Great Firewall, published by Princeton University Press in 2018, was listed as one of the Foreign Affairs Best Books of 2018, was honored with the Goldsmith Book Award, and has been awarded the Best Book Award in the Human Rights Section and Information Technology and Politics Section of the American Political Science Association. I am honored to hold a Chancellor’s Associates Endowed Chair at UCSD.



Text as Data: A New Framework for Machine Learning and the Social Sciences (2022, Princeton University Press) with Justin Grimmer and Brandon Stewart. From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights.

Censored: Distraction and Diversion Inside China's Great Firewall (2018, Princeton University Press) 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.

Working Papers

Waight, Hannah, Yin Yuan, Margaret E. Roberts and Brandon M. Stewart. "Speaking with the State’s Voice: The Decade-Long Growth of Government-Authored News Media in China under Xi Jinping." (2024)

Wu, Xiaohan and Roberts, Margaret E. and Stern, Rachel E. and Liebman, Benjamin L. and Gupta, Amarnath and Sanford, Luke, "Addressing Missingness in Serialized Bureaucratic Data: The Case of Chinese Courts."

Published Papers


  • Jia, Ruixue, Margaret E. Roberts, Ye Wang, and Eddie Yang. “The impact of US–China tensions on US science: Evidence from the NIH investigations.” Proceedings of the National Academy of Sciences 121, no. 19 (2024). Copy here.


  • Liebman, Benjamin, Rachel Stern, Xiaohan Wu, and Margaret E. Roberts. “Rolling Back Transparency in China’s Courts.” Colum. L. Rev. 123 (2023): 2407. Copy here.
  • Appel, Ruth E., Jennifer Pan, and Margaret E. Roberts. “Partisan conflict over content moderation is more than disagreement about facts.” Science Advances 9.44 (2023): eadg6799. Copy here.
  • Chien, Jennifer, Margaret Roberts, and Berk Ustun. “Algorithmic Censoring in Dynamic Learning Systems.” In Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, pp. 1-20. 2023. Copy here.
  • Yang, Eddie, and Margaret E. Roberts. “The Authoritarian Data Problem.” Journal of Democracy 34, no. 4 (2023): 141-150. Copy here.
  • Bischof, Zachary S., Kennedy Pitcher, Esteban Carisimo, Amanda Meng, Rafael Bezerra Nunes, Ramakrishna Padmanabhan, Margaret E. Roberts, Alex C. Snoeren, and Alberto Dainotti. “Destination Unreachable: Characterizing Internet Outages and Shutdowns.” In Proceedings of the ACM SIGCOMM 2023 Conference, pp. 608-621. 2023. Copy here.
  • Hill, Seth J., and Margaret E. Roberts. “Acquiescence bias inflates estimates of conspiratorial beliefs and political misperceptions.” Political Analysis 31.4 (2023): 575-590.  Copy here.


  • Egami, Naoki, Christian J. Fong, Justin Grimmer, Margaret E. Roberts, and Brandon M. Stewart. “How to make causal inferences using texts.” Science Advances 8, no. 42 (2022): eabg2652. Copy here.
  • Feder, A., Keith, K.A., Manzoor, E., Pryzant, R., Sridhar, D., Wood-Doughty, Z., Eisenstein, J., Grimmer, J., Reichart, R., Roberts, M.E. and Stewart, B.M., 2022. Causal inference in natural language processing: Estimation, prediction, interpretation and beyond. Transactions of the Association for Computational Linguistics, 10, pp.1138-1158. Copy here.
  • Grimmer, Justin and Margaret E. Roberts and Brandon Stewart.  Text as Data: A New Framework for Machine Learning and the Social Sciences (2022, Princeton University Press).
  • Chang, Keng-Chi, William R. Hobbs, Margaret E. Roberts, and Zachary C. Steinert-Threlkeld. “COVID-19 increased censorship circumvention and access to sensitive topics in China.” Proceedings of the National Academy of Sciences 119, no. 4 (2022). Copy here.


  • Padmanabhan, Ramakrishna, Arturo Filastò, Maria Xynou, Ram Sundara Raman, Kennedy Middleton, Mingwei Zhang, Doug Madory, Molly Roberts, and Alberto Dainotti. “A multi-perspective view of Internet censorship in Myanmar.” ACM FOCI 2021. Copy here.
  • Stern, Rachel, Benjamin L. Liebman, Margaret E. Roberts, and Alice Z. Wang “Automating Fairness? Artificial Intelligence in the Chinese Courts” Columbia Journal of Transnational Law.
  • Grimmer, Justin, Margaret E. Roberts, and Brandon M. Stewart. “Machine Learning for Social Science: An Agnostic Approach.” Annual Review of Political Science.  Copy here.
  • Eddie Yang and Margaret E. Roberts. 2021. “Censorship of Online Encyclopedias: Implications for NLP Models.” In Conference on Fairness, Accountability, and Transparency (FAccT ‘21). Copy here.


  • Roberts, Margaret E. ”Resilience to online censorship.” Annual Review of Political Science 23 (2020): 401-419. Copy here.
  • Roberts, Margaret E., Brandon M. Stewart, and Richard A. Nielsen. ”Adjusting for confounding with text matching.” American Journal of Political Science 64.4 (2020): 887- 903. Copy here.
  • Liebman, Benjamin L., Margaret E. Roberts, Rachel E. Stern, and Alice Z. Wang. ”Mass digitization of Chinese court decisions: How to use text as data in the field of Chinese law.” Journal of Law and Courts 8, no. 2 (2020): 177-201. Copy here.
  • Pan, Jennifer, and Margaret E. Roberts. ”Censorship’s Effect on Incidental Exposure to Information: Evidence From Wikipedia.” SAGE Open (2020). Copy here.


  • Lutscher, Philipp M., Nils B. Weidmann, Margaret E. Roberts, Mattijs Jonker, Alistair King, and Alberto Dainotti. “At Home and Abroad: The Use of Denial-of-service Attacks during Elections in Nondemocratic Regimes.” Journal of Conflict Resolution (2019). Copy here.
  • Iyad Rahwan, Manuel Cebrian, Nick Obradovich, Josh Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W. Crandall, Nicholas A. Christakis, Iain D. Couzin, Matthew O. Jackson, Nicholas R. Jennings, Ece Kamar, Isabel M. Kloumann, Hugo Larochelle, David Lazer, Richard McElreath, Alan Mislove, David C. Parkes, Alex ‘Sandy’ Pentland, Margaret E. Roberts, Azim Shariff, Joshua B. Tenenbaum & Michael Wellman. “Machine behaviour.” Nature. 2019 Apr;568(7753):477. Copy here.
  • Margaret E. Roberts, Brandon M. Stewart and Dustin Tingley.  “stm: R Package for Structural Topic Models.”  Journal of Statistical Software.  2019. Copy here.
  • Horowitz, Michael, Brandon M. Stewart, Dustin Tingley, Michael Bishop, Laura Resnick Samotin, Margaret Roberts, Welton Chang, Barbara Mellers, and Philip Tetlock. “What makes foreign policy teams tick: Explaining variation in group performance at geopolitical forecasting.” The Journal of Politics 81, no. 4 (2019): 1388-1404. Copy here.


  • Roberts, Margaret E. “What is Political Methodology?.” PS: Political Science & Politics 51.3 (2018): 597-601. Copy here.
  • Hobbs, William R., and Margaret E. Roberts. “How sudden censorship can increase access to information.” American Political Science Review 112.3 (2018): 621-636. Copy here.
  • Roberts, Margaret E.  Censored: Distraction and Diversion Inside China’s Great Firewall.  Princeton University Press.  2018.


  • Gupta, Amarnath, Alice Z. Wang, Kai Lin, Haoshen Hong, Haoran Sun, Benjamin L. Liebman, Rachel E. Stern, Subhasis Dasgupta, and Margaret E. Roberts. “Toward Building a Legal Knowledge-Base of Chinese Judicial Documents for Large-Scale Analytics.” Legal Knowledge and Information Systems (2017): 135.  Copy here.
  • Tucker, Joshua A., Yannis Theocharis, Margaret E. Roberts and Pablo Barberá. 2017.  “From Liberation to Turmoil: Social Media And Democracy.”  Journal of Democracy. Copy here.
  • 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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