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Using Self Organizing Maps to Analyze Demographics and Swing State Voting in the 2008 U.S. Presidential Election

  • Paul T. Pearson
  • Cameron I. Cooper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7477)

Abstract

Emergent self-organizing maps (ESOMs) and k-means clustering are used to cluster counties in each of the states of Florida, Pennsylvania, and Ohio by demographic data from the 2010 United States census. The counties in these clusters are then analyzed for how they voted in the 2008 U.S. Presidential election, and political strategies are discussed that target demographically similar geographical regions based on ESOM results. The ESOM and k-means clusterings are compared and found to be dissimilar by the variation of information distance function.

Keywords

Kohonen self organizing map k-means clustering variation of information United States election 2008 United States Census data 2010 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Paul T. Pearson
    • 1
  • Cameron I. Cooper
    • 2
  1. 1.Hope CollegeHollandUSA
  2. 2.Fort Lewis CollegeDurangoUSA

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