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Margaret E. Roberts
Tytuł
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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
30172013
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
2173*2014
Stm: An R package for structural topic models
ME Roberts, BM Stewart, D Tingley
Journal of statistical software 91, 1-40, 2019
18532019
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
12862017
Machine behaviour
I Rahwan, M Cebrian, N Obradovich, J Bongard, JF Bonnefon, C Breazeal, ...
Nature 568 (7753), 477-486, 2019
11172019
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
8492016
Censored: distraction and diversion inside China's Great Firewall
M Roberts
Princeton University Press, 2018
8212018
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
6692015
Reverse-engineering censorship in China: Randomized experimentation and participant observation
G King, J Pan, ME Roberts
Science 345 (6199), 1251722, 2014
5902014
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
5732013
From liberation to turmoil: Social media and democracy
JA Tucker, Y Theocharis, ME Roberts, P Barberá
Journal of democracy 28 (4), 46-59, 2017
5312017
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
4342015
Text as data: A new framework for machine learning and the social sciences
J Grimmer, ME Roberts, BM Stewart
Princeton University Press, 2022
3342022
Machine learning for social science: An agnostic approach
J Grimmer, ME Roberts, BM Stewart
Annual Review of Political Science 24 (1), 395-419, 2021
2772021
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
2532017
How sudden censorship can increase access to information
WR Hobbs, ME Roberts
American Political Science Review 112 (3), 621-636, 2018
2452018
Navigating the local modes of big data
ME Roberts, BM Stewart, D Tingley
Computational social science 51 (91), 1-40, 2016
2342016
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
2242022
How to make causal inferences using texts
N Egami, CJ Fong, J Grimmer, ME Roberts, BM Stewart
Science Advances 8 (42), eabg2652, 2022
2052022
Adjusting for confounding with text matching
ME Roberts, BM Stewart, RA Nielsen
American Journal of Political Science 64 (4), 887-903, 2020
1352020
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