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Expertise and Bias in Political Communication Networks

Author

Listed:
  • T. K. Ahn
  • Robert Huckfeldt
  • Alexander K. Mayer
  • John Barry Ryan

Abstract

Citizens minimize information costs by obtaining political guidance from others who have already assumed the costs of acquiring and processing political information. A problem occurs because ideal informants, typically characterized by the joint presence of political expertise and shared viewpoints, are frequently unavailable or rare within the groups where individuals are located. Hence, individuals must often look beyond their own group boundaries to find such informants. The problem is that obtaining information from individuals located beyond their own groups produces additional costs. Moreover, the availability of ideal informants varies across groups and settings, with the potential to produce (1) context‐dependent patterns of informant centrality, which in turn generate (2) varying levels of polarization among groups and (3) biases in favor of some groups at the expense of others. The article's analysis is based on a series of small‐group experiments, with aggregate implications addressed using a simple agent‐based model.

Suggested Citation

  • T. K. Ahn & Robert Huckfeldt & Alexander K. Mayer & John Barry Ryan, 2013. "Expertise and Bias in Political Communication Networks," American Journal of Political Science, John Wiley & Sons, vol. 57(2), pages 357-373, April.
  • Handle: RePEc:wly:amposc:v:57:y:2013:i:2:p:357-373
    DOI: 10.1111/j.1540-5907.2012.00625.x
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    Cited by:

    1. Alt, James E. & Jensen, Amalie & Larreguy, Horacio & Lassen, David D. & Marshall, John, 2022. "Diffusing Political Concerns: How Unemployment Information passed between social Ties Influence Danish Voters," TSE Working Papers 22-1292, Toulouse School of Economics (TSE).
    2. T.K. Ahn & John Barry Ryan, 2015. "The overvaluing of expertise in discussion partner choice," Journal of Theoretical Politics, , vol. 27(3), pages 380-400, July.
    3. David Glick & C Daniel Myers, 2015. "Learning from others: an experimental test of Brownian motion uncertainty models," Journal of Theoretical Politics, , vol. 27(4), pages 588-612, October.

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