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How Newspapers Reveal Political Power*


Political science is in large part the study of power, but power itself is difficult to measure. We argue that we can use newspaper coverage—in particular, the relative amount of space devoted to particular subjects in newspapers—to measure the relative power of an important set of political actors and offices. We use a new dataset containing nearly 50 million historical newspaper pages from 2,700 local US newspapers over the years 1877–1977. We define and discuss a measure of power we develop based on observed word frequencies, and we validate it through a series of analyses. Overall, we find that the relative coverage of political actors and of political offices is a strong indicator of political power for the cases we study. To illustrate its usefulness, we then apply the measure to understand when (and where) state party committees lost their power. Taken together, the paper sheds light on the nature of political news coverage and offers both a new dataset and a new measure for studying political power in a wide set of contexts.

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Pamela Ban is a PhD Candidate, Department of Government, 1737 Cambridge Street, CGIS Knafel Building Room 423, Cambridge, MA 02138 ( Alexander Fouirnaies is an Assistant Professor, Harris School of Public Policy, University of Chicago, 1155 E 60th St, Chicago, IL 60637 ( Andrew B. Hall is an Assistant Professor, Department of Political Science, Encina Hall, Stanford University, 616 Serra Mall #100, Stanford, CA 94305 ( James M. Snyder is a Professor, Department of Government, 1737 Cambridge Street, CGIS Knafel Building Room 423, Cambridge, MA 02138 ( For in-depth discussant comments, the authors thank Jordi Blanes i Vidal, Ethan Kaplan, and Daniel Moskowitz. For helpful discussion the authors thank participants of the Princeton/Warwick Political Economy Conference in Venice, Italy, the American Politics Research Workshop at Harvard University, and the PECO Conference in Washington, DC. To view supplementary material for this article, please visit

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Political Science Research and Methods
  • ISSN: 2049-8470
  • EISSN: 2049-8489
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Ban et al. Dataset

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Ban et al. supplementary material 1

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