The Economist’s county-by-county election map is a standout because of its quick-acting slider: you can scroll quite quickly through 64 years of presidential elections. Their analysis also focuses on the urban/rural divide (there’s also a graph). [Benjamin Hennig]
I’ve delayed posting maps of the 2016 U.S. presidential election results because—well, because like many of you I’m still recovering. But here we go. We’ll start with Benjamin Hennig’s cartogram of the results which, as cartograms tend to do, correct for the urban concentrations that made up Hillary Clinton’s vote, and demonstrate the rural nature of Donald Trump’s support. See it at Geographical magazine and Hennig’s website.
Are you used to seeing a big map behind the news anchors during election night coverage? As the Los Angeles Times reports, that’s something that began only in 1976, when NBC News commissioned a 14-foot-high plastic map that lit up (red for Democrats, blue for Republicans—the colors hadn’t been standardized yet) depending on who won the state. [Map Dragons]
While we wait for the results, think back, raise a glass, and remember fondly the meme that came and went so quickly a month or so ago: What if only … voted? Based on FiveThirtyEight maps showing the gender gap in voting intentions (What if only women voted? What if only men voted?) that quickly went viral, similar maps showing gap by race and education
As we approach the first election results of the evening, here are a few maps of the electorate that is doing the voting tonight.
The Washington Post maps the swing counties that could decide the 2016 U.S. presidential election.
The New York Times maps the increasing number of so-called landslide counties—counties where a candidate won by 20 or more percentage points. “The proportion of voters living in landslide counties has steadily increased since 1992, a trend that reflects the growing tendency of like-minded people to live near one another, according to Bill Bishop, a co-author of ‘The Big Sort,’ a 2008 book that identified this phenomenon.”
For all of Donald Trump’s rhetoric about illegal Mexican immigration and competition from China, his supporters don’t seem to be much affected by either. That’s the conclusion of a study by Raul Hinojosa Ojeda of UCLA’s
Geographical magazine explores what they call the “mysterious blue curve” —a narrow swath of Democratic support across the centre of the Deep South. I’ll save you a click: it’s where the African-American voters are concentrated. Geographical, though, goes a bit further back—to the fricking late Cretaceous—to explain why the soil in that area was so amenable to growing cotton, an activity that brought so many slaves to the area in the first place.
Cards on the table: I live in a country where prisoners have the right to vote even while in prison, so the American practice—in 48 of 50 states—of not allowing ex-convicts to vote even after release is both alien and upsetting to me. The New York Times maps the impact of that practice, both in terms of how many people in each state can’t vote due to felony convictions, and in terms of how many African-American adults can’t
Martin Stabe of the Financial Times looks at the paper’s options for displaying the 2016 U.S. presidential results. Which to use, map or cartogram? In the end, neither: they’re going with a dot map—a compromise “that attempts to take the best from the other methods.”
The white underlying geographic map places states in their familiar size, shape and location, allowing them to be identified quickly. Using a cluster of dots rather than a solid fill to represent the outcome ensures that the amount of red and blue on the map accurately reflects states’ weight in the election outcome, rather than the (irrelevant) surface area.
Like the tiled grid cartogram, the number of electoral votes in each state is easy to compare visually without counting or interpreting numbers printed on the map. Because each electoral vote is a discrete mark, it is possible to accurately represent the split electoral votes that are possible in Maine and Nebraska, or the possibility of a faithless elector.
Technical details and source code here.
Previously: A Primer on Election Map Cartography; More Election Cartography Primers.
Vox, earlier this year, used maps to explain the fairly profound ideological shifts in the two major U.S. political parties over their respective histories: How Republicans went from the party of Lincoln to the party of Trump, in 13 maps and 23 maps that explain how Democrats went from the party of racism to the party of Obama.
The Electionland Google Trends map visualizes voting issues during today’s electoral process. It’s based on real-time Google search interest (rather than actual reported problems) in five issues: inactive voter status, long wait times, provisional ballots, voting machine problems and voter intimidation. More about the map and how it works. [Maps Mania]
In 2014 the Washington Post’s Christopher Ingraham reported on the most gerrymandered congressional districts in the United States. The article was accompanied by an interactive map, showing the compactness score Ingraham calculated for each district—the more compact an electoral district, the less likely it’s a gerrymander. [Dave Smith]
(Gerrymandering—manipulating electoral district boundaries for political advantage—has been a frequent topic here on The Map Room. Previous entries include ‘There Is More to Gerrymandering Than Ugly Shapes’, The New York Times on Gerrymandering, Gerrymandering in Florida, More on Gerrymandering and Computer-Generated Districts, Computer-Generated Electoral Districts Redux, Gerrymandering as Computer Game and U.S. Electoral District Ballot Initiatives.)
Before we’re inundated by the results from the 2016 U.S. presidential election, here are a couple of looks back at the 2012 election that explore the results from slightly different angles.
This map shows the county-by-county results but the intensity is by raw vote totals, not percentages: the darker the colour, the more actual votes there are. It’s an attempt to compensate for counties of different sizes, but you still end up with distortions if the county is both large and populous. [Maptitude]
Most Democratic strength is in the cities; most Republican strength is in rural areas. This map depicts the opposites: the urban counties won by Mitt Romney in 2012 and the rural counties where Obama won. [Maps on the Web]
Today, print subscribers to the New York Times were treated to a fold-out map showing a choropleth map of the 2012 election results at the ZIP code level (above). “The map is part of a special election section that aims to help explain the political geography of the United States — identifying where people who are conservative and liberal live and pointing out how physical boundaries, like the Rio Grande and the Cascade Mountains, often align with political ones,” writes the Times’s Alicia Parlapiano.
Parlapiano’s piece is in fact a lengthy tutorial on how to read election maps, along the lines of the pages I linked to in last week’s post on election map cartography—it outlines the problems of state-level election maps and choropleth maps that privilege area over population, for example, and shows some other ways of depicting the results.
It can’t be a coincidence that in today’s Washington Post we have Lazaro Gamio’s article dramatically highlighting the difference between area and population size with comparative maps. Mark Newman’s cartograms also make an appearance.
I can only conclude that both the Times and the Post are making efforts to educate their readers before the election results start coming in, one week from tonight. (Deep breath.)
With less than two weeks before the 2016 U.S. presidential election, it’s time for a refresher on election map cartography, particularly in the context of U.S. presidential elections.
Let’s start with the basics: at All Over the Map, Greg Miller explains the problem with U.S. presidential election maps—big states with few electoral votes look more important than smaller states with more votes—and introduces the idea of the cartogram: a map distorted to account for some variable other than land area.
Here are some cartograms of the 2012 U.S. presidential results (see above). Previously: Cartograms for the 2008 U.S. Presidential Election Results.
Back in 2014, Susan Schulten looked at the map that may have started it all: an 1883 choropleth map of the 1880 U.S. presidential results (see above) that shows results not only on a county-by-county basis, but also the amount the winning candidate won by.
The map may not look advanced today, but in 1883 it broke new ground by enabling Americans to visualize the spatial dynamics of political power. Readers responded enthusiastically. One reviewer pointed to the Republican counties in Arkansas—something left invisible on a map of the Electoral College returns—and wondered what other oddities of geography and history might be uncovered when election returns were more systematically measured. In other words, the map revealed spatial patterns and relationships that might otherwise remain hidden, or only known anecdotally. Perhaps its no coincidence that at the same time the two parties began to launch more coordinated, disciplined, nationwide campaigns, creating a system of two-party rule that we have lived with ever since.
(This map also inverts the modern colours for the two main U.S. political parties: here the Democrats are red and the Republicans are blue. Those colours were standardized only fairly recently.) [Geolounge]
Back to Greg Miller, who has a roundup of different kinds of election maps throughout history, including the maps we’ve seen here so far, Andy Woodruff’s value-by-alpha maps (previously) and others.
For other ways of mapping election results, see this gallery of thematic maps, which includes things like 3D choropleth maps, dot density maps, and all kinds of variations on cartograms and choropleth maps. There’s more than one way to map an election. [Andy Woodruff]
Earlier this month FiveThirtyEight built a county-by-county model showing where both Hillary Clinton and Donald Trump’s “upside potential” — by which they meant where they would each benefit from the shifts in the electoral landscape. Compared to 2012, Clinton is underperforming with non-college-educated whites and Trump is underperforming with Asians, African-Americans, Latinos and college educated whites.
To get a handle on how these shifts could affect the electoral landscape, we modeled how many of Romney’s votes came from college-educated whites and minorities and how many of Obama’s votes came from non-college-educated whites in each state, county and congressional district. The difference between these two vote totals, shown in the map above, can tell us where Clinton and Trump have the most potential to build on 2012.
The authors went on to game out what that might look like in terms of the electoral vote if one in five voters in those shifting groups switched allegiances.
A pronounced gender split is emerging in the 2016 U.S. presidential election. Based on national polls in October, Nate Silver writes, “on average, Clinton leads Trump by 15 percentage points among women while trailing him by 5 points among men. How would that look on the electoral map?” Silver does a quick-and-dirty estimation by adding or subtracting 10 points to/from the FiveThirtyEight forecast. Moving 10 points to Clinton’s column approximates what the electoral map would look like if only women voted:
Moving those 10 points to Trump’s column approximates the results if only men voted:
You’ve almost certainly seen these maps make the rounds of social media. This is where they came from and how they were made.
On the liberal political blog Daily Kos, Stephen Wolf argues that it takes more than a weirdly shaped electoral district to make a gerrymander:
Land does not vote and we can’t judge gerrymanders simply based on geometry. Districts aren’t just abstract shapes on a map, but collections of actual people and voters. Ultimately, the outcomes produced by a particular map matter far more than a map’s appearance. Comparing the actual congressional districts to plausible alternatives in Maryland and other states demonstrates both how gerrymandering is more complex than merely grotesque shapes, and that Maryland is far from the worst partisan gerrymander nationwide.
