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Who Leads? Who Follows? Measuring Issue Attention and Agenda Setting by Legislators and the Mass Public Using Social Media Data



Are legislators responsive to the priorities of the public? Research demonstrates a strong correspondence between the issues about which the public cares and the issues addressed by politicians, but conclusive evidence about who leads whom in setting the political agenda has yet to be uncovered. We answer this question with fine-grained temporal analyses of Twitter messages by legislators and the public during the 113th US Congress. After employing an unsupervised method that classifies tweets sent by legislators and citizens into topics, we use vector autoregression models to explore whose priorities more strongly predict the relationship between citizens and politicians. We find that legislators are more likely to follow, than to lead, discussion of public issues, results that hold even after controlling for the agenda-setting effects of the media. We also find, however, that legislators are more likely to be responsive to their supporters than to the general public.

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This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

Corresponding author

*Pablo Barberá, Assistant Professor, School of International Relations, University of Southern California,
Andreu Casas, Moore-Sloan Research Fellow, Center for Data Science, New York University,
Jonathan Nagler, Professor, Wilf Family Department of Politics, New York University,
**Patrick J. Egan, Associate Professor, Wilf Family Department of Politics, New York University,
††Richard Bonneau, Professor, Center For Genomics and Systems Biology, Courant Institute of Mathematical Sciences, Computer Science Department, and Center for Data Science, New York University; and Flatiron Institute, Center for Computational Biology, Simons Foundation,
‡‡John T. Jost, Professor, Department of Psychology, New York University,
***Joshua A. Tucker, Professor, Wilf Family Department of Politics, New York University,


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We thank Nick Beauchamp, Ken Benoit, Drew Dimmery, Andrew Eggers, Thorsten Faas, Michael Lewis-Beck, Jennifer Pan, Paul Quirk, Molly Roberts, Annelise Russell, Gaurav Sood, David Sontag, Dustin Tingley, and John Wilkerson for their helpful comments and suggestions to previous versions of this paper. We also gratefully acknowledge financial support for the NYU Social Media and Political Participation (SMaPP) lab from the INSPIRE program of the National Science Foundation (Award #1248077), the Bill and Melinda Gates Foundation, the William and Flora Hewlett Foundation, the Rita Allen Foundation, the John S. and James L. Knight Foundation, and Intel. In addition, we would like to thank the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation for their support of the Moore Sloan Data Science Environment, which funded Casas’ time on the project. Replication files are available at the American Political Science Review Dataverse:



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