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Ideal point models analyze lawmakers' votes to quantify their political positions, or ideal points.
Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm
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A spatial model for legislative roll call analysis
Keith T Poole and Howard Rosenthal. 1985 · 1985
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Framing: Toward clarification of a fractured paradigm
Robert M Entman. 1993 · 1993
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Income redistribution and the realignment of American politics
Nolan M McCarty, Keith T Poole, and Howard Rosenthal. 1997 · 1997
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An introduction to variational methods for graphical models
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Learning the parts of objects by non-negative matrix factorization
Daniel D Lee and H Sebastian Seung. 1999 · 1999
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Dynamic ideal point estimation via Markov Chain Monte Carlo for the US Supreme Court, 1953–1999
Andrew D Martin and Kevin M Quinn. 2002 · 1999
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Congress: A political-economic history of roll call voting
Keith T Poole and Howard Rosenthal. 2000 · 2000
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Ideal point estimation with a small number of votes: A random-effects approach
Michael Bailey. 2001 · 2001
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Multidimensional analysis of roll call data via Bayesian simulation: Identification, estimation, inference, and model checking
Simon Jackman. 2001 · 2001
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Estimating Irish party policy positions using computer wordscoring: The 2002 election
Kenneth Benoit and Michael Laver. 2003 · 2002
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Extracting policy positions from political texts using words as data
Michael Laver, Kenneth Benoit, and John Garry. 2003 · 2003
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GaP: A factor model for discrete data
John Canny. 2004 · 2004
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The statistical analysis of roll call data
Joshua Clinton, Simon Jackman, and Douglas Rivers. 2004 · 2004
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Spatial models of parliamentary voting
Keith T Poole. 2005 · 2005
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Framing theory
Dennis Chong and James N Druckman. 2007 · 2007
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The decline of the death penalty and the discovery of innocence
Frank R Baumgartner, Suzanna L De Boef, and Amber E Boydstun. 2008 · 2008
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Measuring explicit political positions of media
Daniel E Ho, Kevin M Quinn, et al. 2008 · 2008
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Understanding wordscores
Will Lowe. 2008 · 2008
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A scaling model for estimating time-series party positions from texts
Jonathan B Slapin and Sven-Oliver Proksch. 2008 · 2008
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Graphical models, exponential families, and variational inference
Martin J Wainwright, Michael I Jordan, et al. 2008 · 2008
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Bayesian inference for nonnegative matrix factorisation models
Ali Taylan Cemgil. 2009 · 2009
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How to avoid pitfalls in statistical analysis of political texts: The case of Germany
Sven-Oliver Proksch and Jonathan B Slapin. 2009 · 2009
The most unkindest cuts: Speaker selection and expressed government dissent during economic crisis
Alexander Herzog and Kenneth Benoit. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2015 · 2015
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Tea Party in the house: A hierarchical ideal point topic model and its application to Republican legislators in the 112th Congress
Viet-An Nguyen, Jordan Boyd-Graber, Philip Resnik, and Kristina Miler. 2015 · 2015
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Deep exponential families
Rajesh Ranganath, Linpeng Tang, Laurent Charlin, and David M Blei. 2015 · 2015
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Bernie Sanders on USA Freedom Act: ”I may well be voting for it,” does not go far enough
RealClearPolitics. 2015 · 2015
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A frame of mind: Using statistical models for detection of framing and agenda setting campaigns
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Predicting legislative roll calls from text
Sean Gerrish and David M Blei. 2011 · 2011
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How they vote: Issue-adjusted models of legislative behavior
Sean Gerrish and David M Blei. 2012 · 2012
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Stochastic variational inference
Matthew D Hoffman, David M Blei, Chong Wang, and John Paisley. 2013 · 2013
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Content-based recommendations with Poisson factorization
Prem K Gopalan, Laurent Charlin, and David M Blei. 2014 · 2014
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Political ideology detection using recursive neural networks
Mohit Iyyer, Peter Enns, Jordan Boyd-Graber, and Philip Resnik. 2014 · 2014
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Auto-encoding variational Bayes
Diederik P Kingma and Max Welling. 2014 · 2014
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Oren Tsur, Dan Calacci, and David Lazer. 2015 · 2015
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Fast estimation of ideal points with massive data
Kosuke Imai, James Lo, and Jonathan Olmsted. 2016 · 2016
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Ideological clarity in multiparty competition: A new measure and test using election manifestos
James Lo, Sven-Oliver Proksch, and Jonathan B Slapin. 2016 · 2016
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Variational inference: A review for statisticians
David M Blei, Alp Kucukelbir, and Jon D McAuliffe. 2017 · 2017
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Leveraging behavioral and social information for weakly supervised collective classification of political discourse on Twitter
Kristen Johnson, Di Jin, and Dan Goldwasser. 2017 · 2017
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Estimating intra-party preferences: Comparing speeches to votes
Daniel Schwarz, Denise Traber, and Kenneth Benoit. 2017 · 2017
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Congressional record for the 43rd-114th Congresses: Parsed speeches and phrase counts
Matthew Gentzkow, Jesse M Shapiro, and Matt Taddy. 2018 · 2018
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Estimating spatial preferences from votes and text
In Song Kim, John Londregan, and Marc Ratkovic. 2018 · 2018
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Neural ideal point estimation network
Kyungwoo Song, Wonsung Lee, and Il-Chul Moon. 2018 · 2018
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Measuring group differences in high-dimensional choices: Method and application to congressional speech
Matthew Gentzkow, Jesse M Shapiro, and Matt Taddy. 2019 · 2019
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Voteview: Congressional roll-call votes database
Jeffrey B. Lewis, Keith Poole, Howard Rosenthal, Adam Boche, Aaron Rudkin, and Luke Sonnet. 2020 · 2020
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U.S. senators tweets from the 114th Congress
VoxGovFEDERAL. 2020 · 2020
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