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How Newspapers Reveal Political Power

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  • Ban, Pamela
  • Fouirnaies, Alexander
  • Hall, Andrew B
  • Snyder, James M

Abstract

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.

Suggested Citation

  • Ban, Pamela & Fouirnaies, Alexander & Hall, Andrew B & Snyder, James M, 2019. "How Newspapers Reveal Political Power," Political Science Research and Methods, Cambridge University Press, vol. 7(4), pages 661-678, October.
  • Handle: RePEc:cup:pscirm:v:7:y:2019:i:04:p:661-678_00
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    Cited by:

    1. Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
    2. Christian R. Grose & Abby K. Wood, 2020. "Randomized experiments by government institutions and American political development," Public Choice, Springer, vol. 185(3), pages 401-413, December.
    3. Massimo Baldini & Andrea Barigazzi, 2023. "Surnames in local newspapers and social mobility," Center for the Analysis of Public Policies (CAPP) 0181, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".

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