Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Handbook of Computational Economics
Handbook of Computational Economics
A comparison of agent-based models of income tax evasion
Social Science Computer Review
Agent-Based Computational Modelling: Applications in Demography, Social, Economic and Environmental Sciences (Contributions to Economics)
Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity)
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The literature on campaigns has considered a number of factors that affect whether and how someone votes, including demographics, campaign strategies, and social milieu. Understanding the dynamics of campaigns, however, is complicated by the fact that researchers cannot observe much of what happens during an election cycle. Typically, studies rely on voter recollections of conversations, contacts, and media exposure. In addition, because data are collected at discrete points in time, most models of voter turnout cannot capture the dynamic nature of an individual芒聙聶s interactions during a campaign cycle. Agent-based models offer a way to overcome these data limitations by allowing us to model the dynamics of voter turnout over the course of many weeks as individuals move back and forth between home and work environments, interacting with neighbors and colleagues. In this article, the authors present an agent-based model of campaign dynamics, VODYS, and conduct three simulations to demonstrate the utility of agent-based models for exploring the effects of contact and context on political behavior.