Figure 2b shows how at County level, the red/blue approach seems to magnify the wrong visual message even further. The use of a Mercator projection (or Web Mercator on a web map) further distorts the areas of the states and compounds the visual problems seen in Figure 1 (Figure 2a). At least Figure 1 used an Albers equal area conic projection…the key part being ‘equal area’ so it ensures that each of the states is in its correct proportion compared to all the others.įigure 2: 2012 US Election results mapped using different techniques (sources: Newman, 2012 Axis Maps, 2012 Nelson, 2012) The data should be normalized to take account of the population distribution because it doesn’t allow for the fact that the large red states generally have smaller populations. The other problem here is that the different sized areas alters the visual prominence of some States relative to others, regardless of how many people or voters live there. Large states become visually dominant and while they might not contribute many electoral college votes to the total they appear visually prominent. The electoral college voting system means that a state will be mapped as either red or blue. There is more red than blue which suggests a win for the Republicans when the opposite was the case. You only have to look at the map and ask the question ‘who won the election?’ to see the problem. This blog entry explores different ways to map election results and describes a different type of map we made to show the 2012 Presidential election results…it’s a multiscale dasymetric dot density web map (viewable on ArcGIS Online).ĭebate about how best to represent election results is nothing new, fuelled principally by the default two-colour map commonly used to show red vs blue States (Figure 1).įigure 1: 2012 US Election result at state level as a unique values map (source: Mark Newman 2012) The patterns we see are as much a product of the boundaries as the voting patterns of real people in real places. ![]() ![]() ![]() We can warp them into cartograms but these sometimes distort geography too much for them to make much sense. Counties) are arbitrary, exhaust space and dictate the visual pattern we see. E very time an election occurs, maps become a key component in telling the story, but what type of map best tells the story of the winners and losers? Red/blue choropleths? Areas shaded in an array of purples? Value by alpha maps? Dot density by County? Ultimately, the areas used (e.g.
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