As the 2008 election draws to a close, political devotees have a
new way to dissect election statistics, thanks to a North Carolina State University computer scientist.
The visualizations created by
Dr. Christopher Healey, associate professor of computer science, go beyond the graphics offered by news outlets like CNN and Fox News. His political graphics show many pieces of electoral information at once, allowing political junkies to get nuanced views of national and state races. He plans to post new political maps on his Web site following the Nov. 4 election, when voters will decide the closely watched presidential contest between Sen. John McCain and Sen. Barack Obama.
We have recently completed collecting and visualizing voter results for U.S. Presidential, U.S. Senate, U.S. House, and state Gubernatorial elections, to study the validity of the common "red state" versus "blue state" classifications.
I am investigating visualization methods that support rapid, accurate, and effective exploration and analysis of large, complex, multidimensional datasets. Many of our techniques exploit the power of the low-level human visual system. This allows much of the analysis work to be performed effortlessly, without requiring focused attention. My results make use of research from an area of cognitive psychology called preattentive processing.
"There is this idea that all
states will vote either Democratic or Republican regardless of the
election," Healey said. "The visualizations we came up with showed that
voters are far more sophisticated than this, and take many different
factors into account when deciding who to vote for."
Healey's maps divide each state or congressional district into four
different sections, which use varying shades of blue and red to
indicate the margin of victory in congressional, gubernatorial and
presidential elections. For example, if North Carolina voters elected a
Democratic governor in a landslide, but preferred a Republican
candidate for president, the varying colors would reflect that.
"The maps used by news networks only reflect one piece of
information, because there isn't a lot of opportunity to explain the
maps," Healey said. "Viewers have to be able to understand the map in
the time that it is on screen. Since people have more time to look at
our maps, we can pack about five or six times the information into our
maps."
Ohio

Pennsylvania

South Carolina

Virginia

Florida

U.S. Election Results
In order to investigate voting patterns across the United States, we decided to visualize winning candidates for four elected offices: the 2004 Presidential, most recent U.S. Senate, 2006 U.S. House, and most recent state Governor's elections. Results were tabulated by congressional district: for each of the 435 districts spread throughout the 50 United States, we collected or estimated which party's candidate the district's voters selected for each of the four offices. Incumbent party losses are particularly important, since they can change the balance of power throughout the country. We therefore wanted to highlight where an incumbent lost during 2006 election cycle for U.S. Senate, U.S. House, and state Governor races.
Although results presented by congressional district are novel and interesting, we also need to show aggregates for each state, for example, which party's candidate won the state for the Presidential, U.S. House, and Governor elections. These aggregates would be difficult or impossible to determine by looking at district results alone. A final state-specific value we wanted to visualize is the number of electoral college votes each state controls, since this affects the state's influence during the Presidential election.
Given these requirements, we built a dataset with two types of data elements representing congressional district results and state-wide results, respectively. Congressional district data elements contain nine data attribute values, and state-wide data elements contain eleven data attributes:
District data attributes:
* A1, President winning party
* A2, President winning percentage
* A3, U.S. Senate winning party
* A4, U.S. Senate winning percentage
* A5, U.S. House winning party
* A6, U.S. House winning percentage
* A7, state Governor winning party
* A8, state Governor winning percentage
* A9, U.S. House incumbent win/loss
State-wide data attributes:
* A1, President winning party
* A2, President winning percentage
* A3, U.S. Senate winning party
* A4, U.S. Senate winning percentage
* A5, party with the majority of the state's U.S. House seats
* A6, percentage of the state's U.S. House seats controlled by the majority party
* A7, state Governor winning party
* A8, state Governor winning percentage
* A9, U.S. Senate incumbent win/loss
* A10, state Governor incumbent win/loss
* A11, state electoral college vote count