The New York Times has covered the 2012 U.S. presidential election in great detail, including the much heralded fivethirtyeight Blog (after the 538 electoral votes) by forecaster Nate Silver. His poll-aggregation model has consistently produced the most accurate forecasts, and called 99 of 100 states correctly in both the 2008 and the 2012 elections.
A popular visualization is the map of the 50 states in colors red (Republican) and blue (Democrat) plus green (Independent). Since most states allocate all their electoral votes to the candidate with the most votes in that state, this state map seems the most important.
This map hardly changed from 2008, only Indiana and North Carolina changed color. Hence the electoral vote result in 2012 (332 Dem – 206 Rep) is similar to that of 2008 (365 Dem – 173 Rep). The visual perception of this map, however, is that there is roughly the same amount of red and blue, with slightly more red than blue. This perception becomes even stronger when looking at the results by county.
Why is the outcome so strongly in favor of the blue (Democrat) when it looks like the majority of the area is red? The answer is found in very uneven population density of the 50 states. Although roughly the same size, California’s (slightly more blue) population density is about 40x higher than Montana’s (mostly red). On the extreme end of this scale, the most densely populated state New Jersey has about 1000x as many people living per square mile as the least densely populated state Alaska. Urban areas have a much higher density of voters than rural areas. The different demographics are such that urban areas tend to vote more blue (Democrat), rural areas tend to vote more red (Republican). The size of the colored area in the above chart would only be a good indicator if the population density was uniform. A great way to compensate visually for this difference can be seen in the third chart published by the NYTimes.
Now the size of the colored circles is proportional to the number of surplus votes for that color in that county. The few blue circles around most major cities are larger and outweigh the many small red circles in rural areas – both optically intuitive and numerically in total. The original map is interactive, giving tooltips when you hover over the circles. For example, in just Los Angeles county there were about 1 million more blue (Democrat) votes than red (Republican).
This optical summation leads to intuitively correct results for the popular votes. The difference in popular vote was about 3.5 million more blue (Democrat) votes or roughly 3%. We see more blue in this delta circle diagram.
Of course, the president is not elected by the popular, but by the electoral votes per state. So no matter how big the Democrat advantage in California may be, there won’t be more than the 55 electoral votes for California. This winner-take-all dynamic of electoral votes by state leads to the outsized influence of swing states which are near the 50%-50% mark on the popular votes. A small lead in the popular vote can lead to a large gain in electoral votes. In extreme cases, a candidate can win the electoral vote and become president despite losing in the popular vote (as happened in 2000 and the very narrow win of Florida by George W. Bush).
Another variation on this theme of visually combining votes and population density information comes from Chris Howard. (This was referenced in an article on theatlanticcities.com by Emily Badger on the spatial divide of urban vs. rural voting preferences which has other election maps as well). The idea is to use shades of blue and red with population density increasing in darker shades of the color, used on a by county map.
A final visualization comes from Nate Silver’s Blog post on November 8. While the % details of this at the time preliminary result may be slightly off (not all votes had been counted yet), the electoral vote counts remain valid.
It shows which swing state [electoral votes] put the blue ticket over the winning line (Colorado ) and which other swing states could have been lost without losing the presidency (Florida , Ohio , Virginia ). It also gives a crude, but somewhat telling indication of where you might want to live if you want to surround yourself by people with blue or red preferences.