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Information gerrymandering in social networks skews collective decision-making

An analysis shows that information flow between individuals in a social network can be ‘gerrymandered’ to skew perceptions of how others in the community will vote — which can alter the outcomes of elections.
By
  1. Carl T. Bergstrom

    1. Carl T. Bergstrom is in the Department of Biology, University of Washington, Seattle, Washington 98105, USA.

  2. Joseph B. Bak-Coleman

    1. Joseph B. Bak-Coleman is in the Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey 08544, USA.

Democracy requires an informed electorate. However, some technological advances change how information flows through society, with serious consequences for the democratic process. Writing in Nature, Stewart et al.1 use experiments and computational models to uncover a previously unrecognized obstacle to democratic decision-making. When social networks become primary conduits of information, the pattern of network connections influences what voters believe about others’ voting intentions. This influence matters, because people shift their own perspectives and voting strategies in response, either through behavioural spread known as social contagion2 or on the basis of strategic considerations.

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Nature 573, 40-41 (2019)

doi: https://doi.org/10.1038/d41586-019-02562-z

Updates & Corrections

  • Correction 08 October 2019: Figure 1c incorrectly stated the numbers of blue and orange nodes that influence each participant in the blue part of the diagram. The graphic has now been updated.

References

  1. Stewart, A. J. et al. Nature 573, 117–121 (2019).

    Article  Google Scholar 

  2. Hodas, N. O. & Lerman, K. Sci. Rep. 4, 4343 (2014).

    Article  PubMed  Google Scholar 

  3. Shearer, E. Social Media Outpaces Print Newspapers in the US as a News Source (Pew Research Center, 2018); go.nature.com/2kgh7eo

    Google Scholar 

  4. Pariser, E. The Filter Bubble (Penguin, 2011).

    Google Scholar 

  5. Ingraham, C. The Washington Post (1 March 2015).

  6. Pattie, C. J. & Johnston, R. J. Environ. Plan. A 37, 1191–1206 (2005).

    Article  Google Scholar 

  7. Napoli, P. M. Telecommun. Policy 39, 751–760 (2015).

    Article  Google Scholar 

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