A computational model of political information processing maps fluctuations in voters' opinions during the 2000 presidential race.

by Trish Barker

In 1948, a Chicago Tribune front-page headline trumpeted "DEWEY DEFEATS TRUMAN," the bold capital letters incorrectly announcing the defeated challenger as the presidential victor. Many newspapers and broadcasters committed the same gaffe in 2000, when a tight race between George W. Bush and Al Gore see-sawed throughout the night of November 7.

These two incidents show the pitfalls of political prognostication. Anticipating which box voters will check on Election Day and understanding how their attitudes and preferences have been shaped are complex challenges. Political scientists Sung-youn Kim, a visiting assistant professor at the University of Iowa, and Milton Lodge and Charles Taber, professors at Stony Brook University in New York, have developed a novel approach to these questions, creating a computational model that simulates the vicissitudes of political opinion. Recent calculations using TeraGrid resources at NCSA and the San Diego Supercomputer Center (SDSC) demonstrated that their model returns results that accord well with actual polling data. Their research was presented at both the 2004 Midwest Political Science Association Conference and the 2004 American Political Science Association Conference.

Integrating Theories

How do people assess candidates? How do campaign events and new information change their views? While there are various theories that address these questions, Kim (then a doctoral student at Stony Brook), Lodge, and Taber saw gaps between existing models and empirical findings. Several theories seemed to partially explain actual political behavior and judgment, but none seemed complete on its own.

"There are two classes of empirical evidence and theories that our model is built upon: the classic cognitive paradigm and the theories of political information processing, including the on-line processing and memory-based processing models," Kim explains. "The model is built by integrating and incorporating what these theories postulate."

Both the on-line and memory-based processing theories--theories regarding how people evaluate political objects, including candidates--were then integrated into the model as its judgment mechanism. The on-line processing theory asserts that the affective summary evaluation (or valence) linked to every object in memory is updated continuously whenever an individual is exposed to new information; the individual maintains a running evaluative tally for each object. Although the original information that entered into the judgment process may be forgotten, the evaluative tallies are immediately accessible. In other words, on seeing or hearing the name "George W. Bush" a person will immediately know how she feels about the candidate, even though she might not be able to say why she feels as she does.

The memory-based processing theory holds that different, often conflicting, considerations and feelings that come to mind at a particular moment influence the evaluation of an object. The accessibility of these concepts in memory determines what comes to mind and thereby influences how those concepts influence evaluation of the object. When a person is asked for his evaluation of Al Gore, for example, his answer will depend in part on which of the many facts about Gore held in his long-term memory are uppermost in his mind at the time.

Kim, Lodge, and Taber developed six algorithms to represent their amalgam of theories in a computational model. They cleverly dubbed this integrated computational model John Q. Public.

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