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[1] Margaret E. Roberts,et al. A Model of Text for Experimentation in the Social Sciences , 2016 .
[2] Will Lowe,et al. A textual Taylor rule: estimating central bank preferences combining topic and scaling methods , 2015, Political Science Research and Methods.
[3] L. Barnes,et al. Making Austerity Popular: The Media and Mass Attitudes toward Fiscal Policy , 2018 .
[4] K. Imai,et al. Dynamic Stochastic Blockmodel Regression for Social Networks : Application to International Conflicts ∗ , 2018 .
[5] Joshua A. Tucker,et al. Elites Tweet to Get Feet Off the Streets: Measuring Regime Social Media Strategies During Protest , 2018, Political Science Research and Methods.
[6] Junyan Jiang. Making Bureaucracy Work: Patronage Networks, Performance Incentives, and Economic Development in China , 2018, American Journal of Political Science.
[7] D. Mimno,et al. Care and Feeding of Topic Models: Problems, Diagnostics, and Improvements , 2014 .
[8] Xiaojin Zhu,et al. Incorporating domain knowledge into topic modeling via Dirichlet Forest priors , 2009, ICML '09.
[9] Amy L. Catalinac,et al. From Pork to Policy: The Rise of Programmatic Campaigning in Japanese Elections , 2016, The Journal of Politics.
[10] Gregory J. Martin,et al. Local News and National Politics , 2019, American Political Science Review.
[11] David M. Mimno,et al. Care and Feeding of Topic Models , 2014, Handbook of Mixed Membership Models and Their Applications.
[12] Dragomir R. Radev,et al. How to Analyze Political Attention with Minimal Assumptions and Costs , 2010 .
[13] Edwin V. Bonilla,et al. Improving Topic Coherence with Regularized Topic Models , 2011, NIPS.
[14] Justin Grimmer,et al. Mirrors for Princes and Sultans: Advice on the Art of Governance in the Medieval Christian and Islamic Worlds , 2018, The Journal of Politics.
[15] Claire Cardie,et al. Multi-aspect Sentiment Analysis with Topic Models , 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.
[16] Edoardo M. Airoldi,et al. Summarizing topical content with word frequency and exclusivity , 2012, ICML 2012.
[17] Economic development in China , 2014 .
[18] Jian Xing,et al. Seed-Guided Topic Model for Document Filtering and Classification , 2018, ACM Trans. Inf. Syst..
[19] Peter A. Chew,et al. Term Weighting Schemes for Latent Dirichlet Allocation , 2010, NAACL.
[20] S. Chib. Estimation and comparison of multiple change-point models , 1998 .
[21] Andrew McCallum,et al. Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression , 2008, UAI.
[22] Douglas Rice. Issue Divisions and US Supreme Court Decision Making , 2017, The Journal of Politics.
[23] David M. Blei,et al. Probabilistic topic models , 2012, Commun. ACM.
[24] Hal Daumé,et al. Incorporating Lexical Priors into Topic Models , 2012, EACL.
[25] Huan Liu,et al. A Novel Measure for Coherence in Statistical Topic Models , 2016, ACL.
[26] Margaret E. Roberts,et al. Computer‐Assisted Keyword and Document Set Discovery from Unstructured Text , 2017 .
[27] Andrew McCallum,et al. Topics over time: a non-Markov continuous-time model of topical trends , 2006, KDD '06.
[28] Margaret E. Roberts,et al. Navigating the Local Modes of Big Data: The Case of Topic Models , 2016, Computational Social Science.
[29] John D. Lafferty,et al. Dynamic topic models , 2006, ICML.
[30] Justin Grimmer,et al. A Bayesian Hierarchical Topic Model for Political Texts: Measuring Expressed Agendas in Senate Press Releases , 2010, Political Analysis.
[31] Justin Grimmer,et al. Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts , 2013, Political Analysis.
[32] David M. Blei,et al. Supervised Topic Models , 2007, NIPS.
[33] Justin Grimmer,et al. Appropriators not Position Takers: The Distorting Effects of Electoral Incentives on Congressional Representation , 2013 .
[34] John M. Olin. Calculating posterior distributions and modal estimates in Markov mixture models , 1996 .
[35] Diyi Yang,et al. Incorporating Word Correlation Knowledge into Topic Modeling , 2015, NAACL.
[36] Wiebke Wagner,et al. Steven Bird, Ewan Klein and Edward Loper: Natural Language Processing with Python, Analyzing Text with the Natural Language Toolkit , 2010, Lang. Resour. Evaluation.
[37] S. Hobolt,et al. Government Responsiveness in the European Union: Evidence From Council Voting , 2017 .
[38] Gang Liu,et al. MetaLDA: A Topic Model that Efficiently Incorporates Meta Information , 2017, 2017 IEEE International Conference on Data Mining (ICDM).
[39] Martin W. Bauer,et al. Qualitative researching with text, image and sound : a practical handbook , 2000 .
[40] Andrew McCallum,et al. Rethinking LDA: Why Priors Matter , 2009, NIPS.
[41] P. Schuler. Position Taking or Position Ducking? A Theory of Public Debate in Single-Party Legislatures , 2018 .
[42] Mark Steyvers,et al. Finding scientific topics , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[43] Ramesh Nallapati,et al. Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora , 2009, EMNLP.
[44] Christian Rauh,et al. Reading Between the Lines: Prediction of Political Violence Using Newspaper Text , 2016, American Political Science Review.
[45] Chong Wang,et al. Reading Tea Leaves: How Humans Interpret Topic Models , 2009, NIPS.
[46] Ding Chen. The economic development of China. , 1980 .
[47] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[48] Haiyan Wang,et al. quanteda: An R package for the quantitative analysis of textual data , 2018, J. Open Source Softw..
[49] D. Hopkins. The Exaggerated Life of Death Panels? The Limited but Real Influence of Elite Rhetoric in the 2009–2010 Health Care Debate , 2017, Political Behavior.
[50] Daichi Mochihashi,et al. Unbounded Slice Sampling , 2020, 2010.01760.
[51] Jennifer Pan,et al. Concealing Corruption: How Chinese Officials Distort Upward Reporting of Online Grievances , 2018, American Political Science Review.
[52] Benjamin E. Bagozzi,et al. The Politics of Scrutiny in Human Rights Monitoring: Evidence from Structural Topic Models of US State Department Human Rights Reports , 2016, Political Science Research and Methods.