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A Computational Model of Political Cognition: The Dynamics of Candidate Evaluation
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A Computational Model of Political Cognition
- The Dynamics of Candidate Evaluation
Kim, Sung-youn
Stony Brook University
Lodge, Milton
Stony Brook University
Taber, Charles
Stony Brook University
Abstract
In this paper, we report on John Q. Public (JQP), a computational model of politicaljudgement which incorporates both cognitive and affective information within an ACT*-likesemantic network and integrates campaign events into candidate evaluations. We developa set of axioms for our underlying theory of information processing, represent those axiomsformally as a computer program written in Common Lisp within the ACT-R framework,and test the internal validity of the model through a series of computational experiments.Using the model, we also simulate the empirical dynamics of candidate evaluation overthe course of the 2000 presidential election campaign using NAES (National AnnenbergElection Survey) 2000 data. The results from computational experiments show that thesingle set of cognitive/affective mechanisms programmed into John Q. Public successfullyreproduce a set of well-known empirical phenomena found in electoral research and researchon political cognition. Specifically, in response to issue and candidate information, JQPreproduces 1) practice, recency, and spreading activation effects on recall, 2) cognitive andattitude priming effects, 3) question order and wording effects, 4) both on-line and memory-based processing, 5) and, most importantly, adjusts its beliefs and attitudes in response tocampaign events. The multiple agents based simulation of empirical dynamics of candidateevaluations in the 2000 eletion show that John Q. Public successfully and simulataneouslyreproduces the empirical dynamics across 5 different ideological groups.
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| | Authors: Kim, Sung-youn., Lodge, Milton. and Taber, Charles. |
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A Computational Model of Political Cognition
- The Dynamics of Candidate Evaluation
Kim, Sung-youn
Stony Brook University
Lodge, Milton
Stony Brook University
Taber, Charles
Stony Brook University
Abstract
In this paper, we report on John Q. Public (JQP), a computational model of political
judgement which incorporates both cognitive and affective information within an ACT*-like
semantic network and integrates campaign events into candidate evaluations. We develop
a set of axioms for our underlying theory of information processing, represent those axioms
formally as a computer program written in Common Lisp within the ACT-R framework,
and test the internal validity of the model through a series of computational experiments.
Using the model, we also simulate the empirical dynamics of candidate evaluation over
the course of the 2000 presidential election campaign using NAES (National Annenberg
Election Survey) 2000 data. The results from computational experiments show that the
single set of cognitive/affective mechanisms programmed into John Q. Public successfully
reproduce a set of well-known empirical phenomena found in electoral research and research
on political cognition. Specifically, in response to issue and candidate information, JQP
reproduces 1) practice, recency, and spreading activation effects on recall, 2) cognitive and
attitude priming effects, 3) question order and wording effects, 4) both on-line and memory-
based processing, 5) and, most importantly, adjusts its beliefs and attitudes in response to
campaign events. The multiple agents based simulation of empirical dynamics of candidate
evaluations in the 2000 eletion show that John Q. Public successfully and simulataneously
reproduces the empirical dynamics across 5 different ideological groups.
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