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NULab for Texts, Maps and Networks
Nick Beauchamp

Nick Beauchamp
I am an Assistant Professor at Northeastern University in the Department of Political Science, the NULab for Text, Maps and Networks, and the Network Science Institute. I received my PhD from the NYU Department of Politics, specializing in U.S. politics (political behavior, campaigns, opinion, political psychology, social media) and political methodology (quantitative text analysis, machine learning, bayesian methods, agent-based models, networks).

My research examines how political opinions form and change as a result of discussion, deliberation and argument in domains such as legislatures, campaigns, social media, and the judiciary, using techniques from machine learning, automated text analysis, and social network analysis. My recent projects explore deliberative quality in online political forums; predict elections using Twitter textual data; test the representativeness of UK legislators based on their text-derived ideology; and visualize the rhetorical structures of political speeches. New projects include experimental methods for optimizing political persusasion, and inferring latent argument strength from political debates.


Research Interests

American Politics: Political Behavior, Campaigns, Congress, Political Psychology, Online and Social Networks

Political Methodology: Quantitative Text Analysis, Machine Learning, Bayesian Methods, Networks, Agent-based Models, Genetic Algorithms


"Winning on the Merits: The Joint Effects of Content and Style on Debate Outcomes," Transactions of the Association for Computational Linguistics, forthcoming 2017 (with Lu Wang, Sarah Shugars, and Kechen Qin)

"Predicting and Interpolating State-level Polls using Twitter Textual Data," American Journal of Political Science 2016

"Measuring Public Opinion with Social Media Data," Book chapter, Oxford Handbook of Polling and Polling Methods, forthcoming, 2017 (with Marko Klasnja, Pablo Barbera, Joshua Tucker and Jonathan Nagler)

"Modeling and Measuring Deliberation Online," Book chapter, Oxford Handbook of Networked Communication, forthcoming, 2017.

"What Terrorist Leaders Want: A Content Analysis of Terrorist Propaganda Videos," Studies in Conflict and Terrorism, 2016 (with Max Abrahms and Joseph Mroszczyk)

Other publications

"Visualizing Biographies of Artists of the Middle East," The Amory Art Show, New York, March 2015

"The State of the Union Address in a Single Image," The Monkey Cage,, January 2015

"A Network Analysis of the Ferguson Witness Reports," The Monkey Cage,, December 2014

"The Ideological Position of Obama's SOTU Relative to Past Presidents," The Monkey Cage,, January 2012

"A Bottom-up Approach to Linguistic Persuasion in Advertising," Research Note in The Political Methodologist, Fall 2011

Nicholas Beauchamp, Henry Brady, Richard Fowles, Aviel Rubin, and Jonathan Taylor, 2004: "Findings of an independent panel on allegations of statistical evidence for fraud during the 2004 Venezuelan Presidential recall referendum," Observing the Venezuela Presidential Recall Referendum: Comprehensive Report, The Carter Center, Atlanta.

Working Papers

(Please feel free to email me for working drafts of any of these papers.)

"Climbing Mount Obamacare: Experimentally Optimized Textual Treatments,"

"Visualizing and Modeling Rhetorical Structures in Individual Documents,"

"Using Text to Scale Legislatures with Uninformative Voting"

"A Bottom-up Approach to Linguistic Persuasion in Advertising"

" 'Someone is Wrong on the Internet': Political Argument as the Exchange of Conceptually Networked Ideas"

"Predicting and Explaining Supreme Court Decisions Using the Texts of Briefs and Oral Arguments"

"Blossom: A new evolutionary strategy optimizer with applications to matching and sampling"

"How do we combine issues? Simultaneously Estimating Spatial Metrics and Utility Functions"

Research in the news

"The Persuasion Principle," Impact: Journal of the Market Research Society, London UK, January 2016

"Inside the Message Machine that Could Make Politicians More Persuasive," NPR's All Things Considered, October 2015

"An Algorithm to Help Politicians Pander," Wired magazine, October 2015

"How to Make Your Speeches Better, Automatically," Pacific Standard magazine, September 2015



Bayesian and Network Statistics, NETS 7983
Introduction to Computational Statistics, PPUA 6301 (Syllabus)
Social Network Analysis, POLS 7334 (Syllabus)
Congress, POLS 3300 and POLS 7251 (Syllabus)
Quantitative Techniques, POLS 2400


Social Networks, Columbia University, Spring 2013
Data Analysis for the Social Sciences, Columbia University, Fall 2012, Spring 2013 (Syllabus)
Math for Political Scientists, Columbia University, Fall 2012 (Syllabus)
Power and Politics in America, Teaching Assistant, NYU, Spring 2011
Math for Political Science, Teaching Assitant, NYU, Fall 2008
Game Theory I, Teaching Assitant, NYU, Spring 2008
Quantitative Methods I, Teaching Assitant, NYU, Fall 2007

Education and Employment

Assistant Professor, Department of Political Science, Northeastern University, 2013-

Lecturer in Discipline, Department of Political Science and Quantitative Methods in the Social Sciences Program, Columbia University, 2012-2013

Ph.D., Political Science, New York University, September 2012

Committee: Jonathan Nagler, Michael Laver, Nathaniel Beck
Dissertation: "Persuasion, Ideology, and Speech: Using automated text analysis to model opinion formation and change"

M.A., Political Science, New York University, 2007

M.A., Literature in English, Johns Hopkins University, 2001

B.A., Honors in Philosophy, Honors in English, Yale University, 1996

For more details, see my C.V.


Nicholas Beauchamp
Department of Political Science
960A Renaissance Park
360 Huntington Avenue
Northeastern University
Boston, MA 02115

Office: RP 931
Email: n D0T beauchamp