How they vote: Issue-adjusted models of legislative behavior

Advances in Neural Information Processing Systems

Volumn 4, Issue , 2012, Pages 2753-2761

  Gerrish, Sean M ^a   Blei, David M ^a  

^a Princeton University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFERENCE ALGORITHM; MULTI-DIMENSIONAL SPACE; POLITICAL ISSUES; PREDICTIVE PERFORMANCE; PROBABILISTIC MODELS; VARIATIONAL METHODS;

INFERENCE ENGINES;

EID: 84877789422     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (26)

1. Keith T. Poole and Howard Rosenthal. Patterns of congressional voting. American Journal of Political Science, 35(1):228-278, February 1991.
2. Simon Jackman. Multidimensional analysis of roll call data via Bayesian simulation: Identification, estimation, inference, and model checking. Political Analysis, 9(3):227-241, 2001.
3. Joshua Clinton, Simon Jackman, and Douglas Rivers. The statistical analysis of roll call data,. American Political Science Review, 98(2):355-370, 2004.
4. Keith T. Poole and Howard Rosenthal. A spatial model for legislative roll call analysis. American Journal of Political Science, pages 357-384, 1985.
5. Andrew D. Martin and Kevin M. Quinn. Dynamic ideal point estimation via Markov chain Monte Carlo for the U.S. Supreme Court, 1953-1999. Political Analysis, 10:134-153, 2002.
6. Daniel Ramage, David Hall, Ramesh Nallapati, and Christopher D. Manning. Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora. Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 2009.
7. David M. Blei, Andrew Y. Ng, and Michael I. Jordan. Latent Dirichlet allocation. Journal of Machine Learning Research, pages 993-1022, 2003.
8. Congressional research service. Available http://www.loc.gov/crsinfo/, 2011.
9. James M. Enelow and Melvin J. Hinich. The Spatial Theory of Voting: An Introduction. Cambridge University Press, New York, 1984.
10. James Albert. Bayesian estimation of normal ogive item response curves using Gibbs sampling. Journal of Educational Statistics, 17:251-269, 1992.
11. James J. Heckman and James M. Snyder. Linear probability models of the demand for attributes with an empirical application to estimating the preferences of legislators. RAND Journal of Economics, 27(0):142-189, 1996.
12. Matt Thomas, Bo Pang, and Lillian Lee. Get out the vote: Determining support or opposition from congressional floor-debate transcripts. In Proceedings of the 2006 Conference on Empirical Methods on Natural Language Processing, 2006.
13. Tae Yano, Noah A. Smith, and John D. Wilkerson. Textual predictors of bill survival in congressional committees. In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics, page 793802, 2012.
14. Sean Gerrish and David Blei. Predicting legislative roll calls from text. Proceedings of the International Conference on Machine Learning, 2011.
15. Eric Wang, Dehong Liu, Jorge Silva, David Dunson, and Lawrence Carin. Joint analysis of time-evolving binary matrices and associated documents. Advances in Neural Information Processing Systems, 23:2370-2378, 2010.
16. Chong Wang and David M. Blei. Collaborative topic modeling for recommending scientific articles. In Proceedings of the 17th international conference on Knowledge Discovery and Data mining, pages 448-456, 2011.
17. Deepak Agarwal and Bee-Chung Chen. fLDA: Matrix factorization through latent Dirichlet allocation. Proceedings of the Third ACM International Conference on Web Search and Data Mining, pages 91-100, 2010.
18. Valen E. Johnson and James H. Albert. Ordinal Data Modeling. Springer-Verlag, New York, 1999.
19. Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, and Lawrence K. Saul. An introduction to variational methods for graphical models. Learning in Graphical Models, pages 183-233, 1999.
20. Herbert Robbins and Sutton Monro. A stochastic approximation method. Annals of Mathematical Statistics, 22(3), September 1951.
21. Leon Bottou and Yann Le Cun. Large scale online learning. In Advances in Neural Information Processing Systems, 2004.
22. Govtrack.us, 2010. Civic Impulse LLC. Available http://www.govtrack.us.
23. Richard F. Fenno Jr. The Congress and America's Future. Prentice-Hall, Englewood Cliffs, NJ, 1965.
24. Gary W. Cox and Mathew D. McCubbins. Legislative Leviathon. University of California Press., 1993.
25. Gary W. Cox and Keith T. Poole. On measuring partisanship in roll-call voting: The U.S. House of Representatives, 1877-1999. American Journal of Political Science, 46(3):pp. 477-489, 2002.
26. Gary W. Cox and Mathew D. McCubbins. Setting the Agenda: Responsible Party Government in the U.S. House of Representatives. Cambridge University Press, 2005.