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The Forum

A Journal of Applied Research in Contemporary Politics

Ed. by Disalvo, Daniel / Stonecash, Jeffrey

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Volume 14, Issue 4 (Dec 2016)


Algorithmic Opportunity: Digital Advertising and Inequality in Political Involvement

Young Mie Kim
  • Corresponding author
  • Associate Professor, University of Wisconsin-Madison, Madison, WI, USA
  • Email:
Published Online: 2017-02-22 | DOI: https://doi.org/10.1515/for-2016-0034


Contemporary digital advertising operates through algorithms – a data-driven logic created by the constant loop between a voter’s voluntary choices and campaigns’ strategic feedback on these choices. By paying attention to the logic of digital advertising, I discuss how digital advertising algorithms adjudicate consequential decisions that broadly affect political involvement. I argue digital advertising limits algorithmic opportunity to access and acquire political information. Voters are strategically defined, and information inequality is created between the arbitrarily defined “strategically important” and “strategically unimportant.” Discriminately defined by campaigns, different voters receive different information, thereby engaging differently in politics. To illuminate main points, an exploratory analysis of empirical data that “reverse engineered” the algorithms of digital advertising is presented. I conclude that contemporary digital advertising perhaps propels inequality of political involvement and polarizes the electorate.


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About the article

Young Mie Kim

Young Mie Kim (PhD, University of Illinois at Urbana-Champaign) is an Associate Professor of the School of Journalism and Mass Communication and faculty affiliate of the Department of Political Science at the University of Wisconsin-Madison. Kim’s research centers on the role digital media play in citizen competence and participation.

Published Online: 2017-02-22

Published in Print: 2016-12-01

Citation Information: The Forum, ISSN (Online) 1540-8884, ISSN (Print) 2194-6183, DOI: https://doi.org/10.1515/for-2016-0034. Export Citation

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