From factors to actors: Computational sociology and agent-based modeling
From factors to actors: Computational sociology and agent-based modeling
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DOI：
10.1146/annurev.soc.28.110601.141117
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发表时间：
2002-01-01
影响因子：
10.5
通讯作者：
Willer, R
中科院分区：
文献类型：
--
作者：
Macy, MW;Willer, R
社会学家经常将社会过程建模为变量之间的相互作用。我们回顾了一种替代方法，该方法将社会生活建模为适应主体之间的互动，这些主体根据自己受到的影响相互影响。这些基于主体的模型(ABM)显示了简单和可预测的局部互动如何产生熟悉但神秘的全球模式，如信息传播、规范的出现、公约的协调或参与集体行动。新兴的社会模式也可以意外地出现，然后就像革命、市场崩盘、时尚和助长狂热一样，戏剧性地转变或消失。ABM提供了理论杠杆，其中感兴趣的全球模式不仅仅是单个属性的集合，但同时，如果没有关系层面上微观基础的自下而上的动态模型，就无法理解新兴模式。我们从计算社会学中从“因素”到“行为者”转变的一个简短的历史草图开始，展示了基于主体的建模与早期的计算机模拟的社会学使用有何根本不同。然后，我们回顾了最近关于从地方互动中出现社会结构和社会秩序的贡献。尽管社会学在欣赏这一新的方法论方面落后于其他社会科学，但在我们审查的论文中，社会学的独特贡献是显而易见的。首先，理论兴趣集中在塑造和被代理人互动塑造的动态社交网络上。其次，ABM被用来进行虚拟实验，通过操纵网络拓扑、社会分层或空间流动性等结构性因素来测试宏观社会学理论。我们以一系列建议来结束我们的审查，以实现这一方法的丰富社会学潜力。
Sociologists often model social processes as interactions among variables. We review an alternative approach that models social life as interactions among adaptive agents who influence one another in response to the influence they receive. These agent-based models (ABMs) show how simple and predictable local interactions can generate familiar but enigmatic global patterns, such as the diffusion of information, emergence of norms, coordination of conventions, or participation in collective action. Emergent social patterns can also appear unexpectedly and then just as dramatically transform or disappear, as happens in revolutions, market crashes, fads, and feeding frenzies. ABMs provide theoretical leverage where the global patterns of interest are more than the aggregation of individual attributes, but at the same time, the emergent pattern cannot be understood without a bottom up dynamical model of the microfoundations at the relational level. We begin with a brief historical sketch of the shift from "factors" to "actors" in computational sociology that shows how agent-based modeling differs fundamentally from earlier sociological uses of computer simulation. We then review recent contributions focused on the emergence of social structure and social order out of local interaction. Although sociology has lagged behind other social sciences in appreciating this new methodology, a distinctive sociological contribution is evident in the papers we review. First, theoretical interest focuses on dynamic social networks that shape and are shaped by agent interaction. Second, ABMs are used to perform virtual experiments that test macrosociological theories by manipulating structural factors like network topology, social stratification, or spatial mobility. We conclude our review with a series of recommendations for realizing the rich sociological potential of this approach.