Doctoral Dissertation Research in Political Science: A Computational Model of Political Attitude and Behavior

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A more comprehensive model of human mental process is possible and necessary to improve our understanding of ordinary citizens' political judgment and behavior. Here, I develop a computational model of mental process, named as John Q. Public, that incorporates both cognitive and affective mechanism, and integrates on-line processing and memory-based model. Using the model, I will simultaneously reproduce and explain the well-known empirical phenomena in public opinion and voting behaviors that have been only separately and partially accounted for empirically. That is, I will show that the well-known empirical regularities - such as cognitive and attitude priming effect, dual-process, question order and wording effects in survey research, and on-line processing - are generated by a single, principled set of cognitive/affective mechanisms. By doing so, the study also shows that the two major competitive theories of political judgments, on-line processing and memory-based model, are in fact interdependent and should be integrated into a more general theory. The study also introduces a 'fully' cognitive model of strategic behavior. Specifically, I put multiple John Q. Publics as players in a repeated social dilemma game and try to explain, in a 'cognitively feasible' way, the dynamics of cooperation observed in experimental data. Broader Impacts: Can help broaden understanding of ordinary citizens' political judgment and voting behavior.