Bailey, Michael A. Strezhnev, Anton and Voeten, Erik 2017. Estimating Dynamic State Preferences from United Nations Voting Data. Journal of Conflict Resolution, Vol. 61, Issue. 2, p. 430.
Bui, Xuan Vu, Tu and Than, Khoat 2017. Advances in Information and Communication Technology.
Chong, Mark and Choy, Murphy 2016. The Social Amplification of Haze-Related Risks on the Internet. Health Communication, p. 1.
Clementson, David E. 2016. Why Do We Think Politicians Are So Evasive? Insight From Theories of Equivocation and Deception, With a Content Analysis of U.S. Presidential Debates, 1996-2012. Journal of Language and Social Psychology, Vol. 35, Issue. 3, p. 247.
Cormack, Lindsey 2016. Extremity in Congress: Communications versus Votes. Legislative Studies Quarterly, Vol. 41, Issue. 3, p. 575.
Evans, James A. and Aceves, Pedro 2016. Machine Translation: Mining Text for Social Theory. Annual Review of Sociology, Vol. 42, Issue. 1, p. 21.
Fowles, Jacob Frederickson, H. George and Koppell, Jonathan G. S. 2016. University Rankings: Evidence and a Conceptual Framework. Public Administration Review, Vol. 76, Issue. 5, p. 790.
Hagen, Loni Harrison, Teresa M. Uzuner, Özlem May, William Fake, Tim and Katragadda, Satya 2016. E-petition popularity: Do linguistic and semantic factors matter?. Government Information Quarterly, Vol. 33, Issue. 4, p. 783.
Jones, Jennifer J. 2016. Talk “Like a Man”: The Linguistic Styles of Hillary Clinton, 1992–2013. Perspectives on Politics, Vol. 14, Issue. 03, p. 625.
Kim, Dongwook Kang, Juyoung and Lim, Jay Ick 2016. Comparative Analysis of Job Satisfaction Factors, Using LDA Topic Modeling by Industries : The Case Study of Job Planet Reviews. Journal of the Korea society of IT services, Vol. 15, Issue. 3, p. 157.
Klüver, Heike and Sagarzazu, Iñaki 2016. Setting the Agenda or Responding to Voters? Political Parties, Voters and Issue Attention. West European Politics, Vol. 39, Issue. 2, p. 380.
Lafaye, Caroline Guibet and Brochard, Pierre 2016. La radicalisation vue par la presse – Fluctuation d’une représentation. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, Vol. 131, Issue. 1, p. 25.
Lin, Yu-Ru Margolin, Drew and Lazer, David 2016. Uncovering social semantics from textual traces: A theory-driven approach and evidence from public statements of U.S. Members of Congress. Journal of the Association for Information Science and Technology, Vol. 67, Issue. 9, p. 2072.
Lo, James Proksch, Sven-Oliver and Slapin, Jonathan B. 2016. Ideological Clarity in Multiparty Competition: A New Measure and Test Using Election Manifestos. British Journal of Political Science, Vol. 46, Issue. 03, p. 591.
Merz, Nicolas Regel, Sven and Lewandowski, Jirka 2016. The Manifesto Corpus: A new resource for research on political parties and quantitative text analysis. Research & Politics, Vol. 3, Issue. 2, p. 205316801664334.
Miratrix, Luke and Ackerman, Robin 2016. Conducting sparse feature selection on arbitrarily long phrases in text corpora with a focus on interpretability. Statistical Analysis and Data Mining: The ASA Data Science Journal, Vol. 9, Issue. 6, p. 435.
Nowlin, Matthew C. 2016. Modeling Issue Definitions Using Quantitative Text Analysis. Policy Studies Journal, Vol. 44, Issue. 3, p. 309.
Pardos-Prado, Sergi and Sagarzazu, Iñaki 2016. The Political Conditioning of Subjective Economic Evaluations: The Role of Party Discourse. British Journal of Political Science, Vol. 46, Issue. 04, p. 799.
Roberts, Margaret E. Stewart, Brandon M. and Airoldi, Edoardo M. 2016. A Model of Text for Experimentation in the Social Sciences. Journal of the American Statistical Association, Vol. 111, Issue. 515, p. 988.
Political scientists lack methods to efficiently measure the priorities political actors emphasize in statements. To address this limitation, I introduce a statistical model that attends to the structure of political rhetoric when measuring expressed priorities: statements are naturally organized by author. The expressed agenda model exploits this structure to simultaneously estimate the topics in the texts, as well as the attention political actors allocate to the estimated topics. I apply the method to a collection of over 24,000 press releases from senators from 2007, which I demonstrate is an ideal medium to measure how senators explain their work in Washington to constituents. A set of examples validates the estimated priorities and demonstrates their usefulness for testing theories of how members of Congress communicate with constituents. The statistical model and its extensions will be made available in a forthcoming free software package for the R computing language.
Author's note: I thank the Center for American Political Studies and the Institute for Quantitative Social Science for financial support. I have benefited from conversations with Ken Benoit, Matt Blackwell, Daniel Carpenter, Jacqueline Chattopadhyay, Andrew Coe, Brian Feinstein, Rob Franzese, Claudine Gay, Jeff Gill, David Hadley, Frank Howland, Emily Hickey, D. Sunshine Hillygus, Daniel Hopkins, Michael Kellerman, Gary King, Burt Monroe, Clayton Nall, Stephen Purpura, Kevin Quinn, Brandon Stewart, seminar participants at Harvard University, participants at the 2008 Summer Political Methodology meeting, and 2009 Southern Political Science Association meeting.
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