| How censorship in China allows government criticism but silences collective expression G King, J Pan, ME Roberts American political science Review 107 (2), 326-343, 2013 | 3067 | 2013 |
| Topic models for open ended survey responses with applications to experiments ME Roberts, BM Stewart, D Tingley, C Lucas, J Leder-Luis, B Albertson, ... American Journal of Political Science 58 (4), 1064-1082, 2014 | 2233* | 2014 |
| Stm: An R package for structural topic models ME Roberts, BM Stewart, D Tingley Journal of statistical software 91, 1-40, 2019 | 1923 | 2019 |
| How the Chinese government fabricates social media posts for strategic distraction, not engaged argument G King, J Pan, ME Roberts American political science review 111 (3), 484-501, 2017 | 1314 | 2017 |
| Machine behaviour I Rahwan, M Cebrian, N Obradovich, J Bongard, JF Bonnefon, C Breazeal, ... Nature 568 (7753), 477-486, 2019 | 1181 | 2019 |
| A model of text for experimentation in the social sciences ME Roberts, BM Stewart, EM Airoldi Journal of the American Statistical Association 111 (515), 988-1003, 2016 | 871 | 2016 |
| Censored: distraction and diversion inside China's Great Firewall M Roberts Princeton University Press, 2018 | 835 | 2018 |
| Computer-assisted text analysis for comparative politics C Lucas, RA Nielsen, ME Roberts, BM Stewart, A Storer, D Tingley Political Analysis 23 (2), 254-277, 2015 | 681 | 2015 |
| Reverse-engineering censorship in China: Randomized experimentation and participant observation G King, J Pan, ME Roberts Science 345 (6199), 1251722, 2014 | 600 | 2014 |
| The structural topic model and applied social science ME Roberts, BM Stewart, D Tingley, EM Airoldi Advances in neural information processing systems workshop on topic models …, 2013 | 586 | 2013 |
| From liberation to turmoil: Social media and democracy JA Tucker, Y Theocharis, ME Roberts, P Barberá Journal of democracy 28 (4), 46-59, 2017 | 557 | 2017 |
| How robust standard errors expose methodological problems they do not fix, and what to do about it G King, ME Roberts Political Analysis 23 (2), 159-179, 2015 | 439 | 2015 |
| Text as data: A new framework for machine learning and the social sciences J Grimmer, ME Roberts, BM Stewart Princeton University Press, 2022 | 371 | 2022 |
| Machine learning for social science: An agnostic approach J Grimmer, ME Roberts, BM Stewart Annual Review of Political Science 24 (1), 395-419, 2021 | 291 | 2021 |
| Computer‐assisted keyword and document set discovery from unstructured text G King, P Lam, ME Roberts American Journal of Political Science 61 (4), 971-988, 2017 | 261 | 2017 |
| How sudden censorship can increase access to information WR Hobbs, ME Roberts American Political Science Review 112 (3), 621-636, 2018 | 251 | 2018 |
| Causal inference in natural language processing: Estimation, prediction, interpretation and beyond A Feder, KA Keith, E Manzoor, R Pryzant, D Sridhar, Z Wood-Doughty, ... Transactions of the Association for Computational Linguistics 10, 1138-1158, 2022 | 242 | 2022 |
| Navigating the local modes of big data ME Roberts, BM Stewart, D Tingley Computational social science 51 (91), 1-40, 2016 | 238 | 2016 |
| How to make causal inferences using texts N Egami, CJ Fong, J Grimmer, ME Roberts, BM Stewart Science Advances 8 (42), eabg2652, 2022 | 212 | 2022 |
| Mass digitization of Chinese court decisions: How to use text as data in the field of Chinese law BL Liebman, ME Roberts, RE Stern, AZ Wang Journal of Law and Courts 8 (2), 177-201, 2020 | 140 | 2020 |
